diff --git a/torax/_src/pedestal_model/pydantic_model.py b/torax/_src/pedestal_model/pydantic_model.py
index e251f1f6a..0a9f90539 100644
--- a/torax/_src/pedestal_model/pydantic_model.py
+++ b/torax/_src/pedestal_model/pydantic_model.py
@@ -26,6 +26,7 @@
 from torax._src.pedestal_model import set_pped_tpedratio_nped
 from torax._src.pedestal_model import set_tped_nped
 from torax._src.pedestal_model.formation import power_scaling_formation_model
+from torax._src.pedestal_model.saturation import ballooning_stability_saturation_model
 from torax._src.pedestal_model.saturation import profile_value_saturation_model
 from torax._src.torax_pydantic import torax_pydantic
 
@@ -207,9 +208,72 @@ def build_runtime_params(
     )
 
 
+class BallooningStabilitySaturation(torax_pydantic.BaseModelFrozen):
+  """Configuration for BallooningStabilitySaturation model.
+
+  This saturation model triggers an increase in pedestal transport when the
+  normalized pressure gradient alpha is above alpha_crit.
+
+  The formula is
+    transport_multiplier = 1 + alpha * base_multiplier,
+  where alpha is a softplus function of the normalized deviation from the target
+  value, with given steepness and offset:
+    x = (current - target) / target - offset
+    alpha = log(1 + exp(steepness * x))
+
+  Attributes:
+    alpha_crit: Margin above which transport is enhanced.
+    steepness: Scaling factor applied to the argument of the softplus function,
+      setting the steepness of the smooth saturation function. Decrease for a
+      smoother saturation, which may be more numerically stable but may lead to
+      starting saturation at a temperature or density below the target values.
+    offset: Bias applied to the argument of the softplus function, setting the
+      dimensionless offset of the saturation window. Increase to start
+      saturation at a higher temperature or density.
+    base_multiplier: The base value of the transport multiplier. Increase for
+      stronger increases in transport once saturation starts.
+  """
+
+  model_name: Annotated[
+      Literal["ballooning_stability"], torax_pydantic.JAX_STATIC
+  ] = "ballooning_stability"
+  alpha_crit: pydantic.PositiveFloat = 1.0
+  steepness: pydantic.PositiveFloat = 100.0
+  # Default offset is > 0 as otherwise saturation starts too early. This is
+  # because the softplus function is nonzero before the argument is zero.
+  offset: Annotated[
+      array_typing.FloatScalar, pydantic.Field(ge=-10.0, le=10.0)
+  ] = 0.1
+  base_multiplier: Annotated[
+      array_typing.FloatScalar, pydantic.Field(gt=1.0)
+  ] = 1e6
+
+  def build_saturation_model(
+      self,
+  ) -> ballooning_stability_saturation_model.BallooningStabilitySaturationModel:
+    return (
+        ballooning_stability_saturation_model.BallooningStabilitySaturationModel()
+    )
+
+  def build_runtime_params(
+      self, t: chex.Numeric
+  ) -> (
+      ballooning_stability_saturation_model.BallooningStabilitySaturationRuntimeParams
+  ):
+    del t
+    return ballooning_stability_saturation_model.BallooningStabilitySaturationRuntimeParams(
+        alpha_crit=self.alpha_crit,
+        steepness=self.steepness,
+        offset=self.offset,
+        base_multiplier=self.base_multiplier,
+    )
+
+
 # For new formation and saturation models, add to these TypeAliases via Union.
 FormationConfig: TypeAlias = DelabieScalingFormation | MartinScalingFormation
-SaturationConfig: TypeAlias = ProfileValueSaturation
+SaturationConfig: TypeAlias = (
+    ProfileValueSaturation | BallooningStabilitySaturation
+)
 
 
 class BasePedestal(torax_pydantic.BaseModelFrozen, abc.ABC):
diff --git a/torax/_src/pedestal_model/saturation/ballooning_stability_saturation_model.py b/torax/_src/pedestal_model/saturation/ballooning_stability_saturation_model.py
new file mode 100644
index 000000000..d06521f9d
--- /dev/null
+++ b/torax/_src/pedestal_model/saturation/ballooning_stability_saturation_model.py
@@ -0,0 +1,143 @@
+# Copyright 2026 DeepMind Technologies Limited
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Saturation model based on ballooning stability limit."""
+
+import dataclasses
+import jax
+import jax.numpy as jnp
+from torax._src import array_typing
+from torax._src import constants
+from torax._src import math_utils
+from torax._src import state
+from torax._src.config import runtime_params as runtime_params_lib
+from torax._src.geometry import geometry
+from torax._src.pedestal_model import pedestal_model_output
+from torax._src.pedestal_model import runtime_params as pedestal_runtime_params_lib
+from torax._src.pedestal_model.saturation import base
+from torax._src.physics import formulas
+
+# pylint: disable=invalid-name
+
+
+def calculate_normalized_pressure_gradient(
+    core_profiles: state.CoreProfiles,
+    geo: geometry.Geometry,
+) -> array_typing.FloatVector:
+  """Calculates the normalized pressure gradient (alpha).
+
+  Equation:
+    alpha = -2*mu_0 * (dV/dpsi) * (1/(2*pi)^2) * sqrt(V / (2*pi^2*R_0)) *
+    (dp/dpsi)
+
+  Args:
+    core_profiles: CoreProfiles object containing information on pressures and
+      psi.
+    geo: Geometry object.
+
+  Returns:
+    alpha: Normalized pressure gradient evaluated on the face grid.
+  """
+  dp_dpsi = formulas.calc_pprime(core_profiles)
+  dpsi_drhon = core_profiles.psi.face_grad()
+  # vpr is dV/drhon, so dV/dpsi = vpr / dpsi/drhon
+  dV_dpsi = math_utils.safe_divide(geo.vpr_face, dpsi_drhon)
+
+  # Plasma volume enclosed by the flux surface (V) and major radius (R_0)
+  V = geo.volume_face
+  R_0 = geo.R_major
+
+  # Calculate alpha
+  return (
+      -2.0
+      * constants.CONSTANTS.mu_0
+      * dV_dpsi
+      * (1.0 / (2.0 * jnp.pi) ** 2)
+      * jnp.sqrt(V / (2.0 * jnp.pi**2 * R_0))
+      * dp_dpsi
+  )
+
+
+@jax.tree_util.register_dataclass
+@dataclasses.dataclass(frozen=True)
+class BallooningStabilitySaturationRuntimeParams(
+    pedestal_runtime_params_lib.SaturationRuntimeParams
+):
+  """Runtime params for ballooning stability saturation models."""
+
+  alpha_crit: array_typing.FloatScalar
+
+
+@dataclasses.dataclass(frozen=True, eq=False)
+class BallooningStabilitySaturationModel(base.SaturationModel):
+  """Saturation model based on the maximum pressure gradient alpha_crit."""
+
+  def __call__(
+      self,
+      runtime_params: runtime_params_lib.RuntimeParams,
+      geo: geometry.Geometry,
+      core_profiles: state.CoreProfiles,
+      pedestal_output: pedestal_model_output.PedestalModelOutput,
+  ) -> array_typing.FloatScalar:
+    """Calculates transport increase multipliers."""
+    assert isinstance(
+        runtime_params.pedestal.saturation,
+        BallooningStabilitySaturationRuntimeParams,
+    )
+
+    alpha = calculate_normalized_pressure_gradient(core_profiles, geo)
+    max_alpha_ped = jnp.max(
+        jnp.where(
+            geo.rho_face_norm >= pedestal_output.rho_norm_ped_top, alpha, 0.0
+        )
+    )
+    multiplier = self._calculate_multiplier(
+        current=max_alpha_ped,
+        target=runtime_params.pedestal.saturation.alpha_crit,
+        pedestal_runtime_params=runtime_params.pedestal,
+    )
+    return pedestal_model_output.TransportMultipliers(
+        chi_e_multiplier=multiplier,
+        chi_i_multiplier=multiplier,
+        D_e_multiplier=multiplier,
+        v_e_multiplier=multiplier,
+    )
+
+  def _calculate_multiplier(
+      self,
+      current: array_typing.FloatScalar,
+      target: array_typing.FloatScalar,
+      pedestal_runtime_params: pedestal_runtime_params_lib.RuntimeParams,
+  ) -> array_typing.FloatScalar:
+    """Calculates the transport increase multiplier.
+
+    If current >> target, multiplier -> infinity.
+    If current << target, multiplier -> 1.
+
+    Args:
+      current: The current value of the profile at the pedestal top.
+      target: The target value of the profile at the pedestal top.
+      pedestal_runtime_params: The runtime parameters for the pedestal model.
+
+    Returns:
+      The transport increase multiplier.
+    """
+    steepness = pedestal_runtime_params.saturation.steepness
+    offset = pedestal_runtime_params.saturation.offset
+    base_multiplier = pedestal_runtime_params.saturation.base_multiplier
+    normalized_deviation = (current - target) / target - offset
+    transport_multiplier = 1 + base_multiplier * jax.nn.softplus(
+        normalized_deviation * steepness
+    )
+    return transport_multiplier
diff --git a/torax/_src/pedestal_model/saturation/tests/ballooning_stability_saturation_model_test.py b/torax/_src/pedestal_model/saturation/tests/ballooning_stability_saturation_model_test.py
new file mode 100644
index 000000000..8d694fa2d
--- /dev/null
+++ b/torax/_src/pedestal_model/saturation/tests/ballooning_stability_saturation_model_test.py
@@ -0,0 +1,123 @@
+# Copyright 2026 DeepMind Technologies Limited
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import dataclasses
+from absl.testing import absltest
+from absl.testing import parameterized
+import numpy as np
+from torax._src.config import build_runtime_params
+from torax._src.core_profiles import initialization
+from torax._src.pedestal_model import pedestal_model_output
+from torax._src.pedestal_model.saturation import ballooning_stability_saturation_model
+from torax._src.test_utils import default_configs
+from torax._src.torax_pydantic import model_config
+
+# pylint: disable=invalid-name
+
+
+class BallooningStabilitySaturationModelTest(parameterized.TestCase):
+
+  def setUp(self):
+    super().setUp()
+    config = default_configs.get_default_config_dict()
+    # Add ballooning stability config with a default value for alpha_crit.
+    config['pedestal']['saturation_model'] = {
+        'model_name': 'ballooning_stability',
+        'alpha_crit': 1.0,  # Will be overridden in specific tests.
+    }
+    self.torax_config = model_config.ToraxConfig.from_dict(config)
+    self.provider = build_runtime_params.RuntimeParamsProvider.from_config(
+        self.torax_config
+    )
+    self.runtime_params = self.provider(t=0.0)
+    self.geo = self.torax_config.geometry.build_provider(t=0.0)
+    self.source_models = self.torax_config.sources.build_models()
+    self.neoclassical_models = self.torax_config.neoclassical.build_models()
+    self.core_profiles = initialization.initial_core_profiles(
+        self.runtime_params,
+        self.geo,
+        self.source_models,
+        self.neoclassical_models,
+    )
+
+  @parameterized.named_parameters(
+      dict(
+          testcase_name='active',
+          # Low alpha_crit -> saturation is active.
+          alpha_crit=1e-3,
+      ),
+      dict(
+          testcase_name='inactive',
+          # High alpha_crit -> saturation is inactive.
+          alpha_crit=1e3,
+      ),
+  )
+  def test_saturation_multiplier(
+      self,
+      alpha_crit: float,
+  ):
+    assert isinstance(
+        self.runtime_params.pedestal.saturation,
+        ballooning_stability_saturation_model.BallooningStabilitySaturationRuntimeParams,
+    )
+    saturation_model = (
+        ballooning_stability_saturation_model.BallooningStabilitySaturationModel()
+    )
+
+    # For this test, we put the pedestal top at the last grid point.
+    pedestal_output = pedestal_model_output.PedestalModelOutput(
+        rho_norm_ped_top=1.0,
+        rho_norm_ped_top_idx=-1,
+        # The following values are not used in the saturation model.
+        T_i_ped=1.0,
+        T_e_ped=1.0,
+        n_e_ped=1.0,
+    )
+
+    # Set alpha_crit in the runtime params.
+    new_saturation_params = dataclasses.replace(
+        self.runtime_params.pedestal.saturation,
+        alpha_crit=alpha_crit,
+        steepness=self.runtime_params.pedestal.saturation.steepness,
+        offset=self.runtime_params.pedestal.saturation.offset,
+        base_multiplier=self.runtime_params.pedestal.saturation.base_multiplier,
+    )
+    new_pedestal_params = dataclasses.replace(
+        self.runtime_params.pedestal, saturation=new_saturation_params
+    )
+    runtime_params = dataclasses.replace(
+        self.runtime_params, pedestal=new_pedestal_params
+    )
+
+    # Get actual alpha in the pedestal.
+    alpha = ballooning_stability_saturation_model.calculate_normalized_pressure_gradient(
+        self.core_profiles, self.geo
+    )
+    max_alpha_ped = alpha[-1]
+
+    # Calculate the multiplier.
+    transport_multipliers = saturation_model(
+        runtime_params,
+        self.geo,
+        self.core_profiles,
+        pedestal_output,
+    )
+
+    if max_alpha_ped < alpha_crit:
+      np.testing.assert_allclose(transport_multipliers.chi_e_multiplier, 1.0)
+    else:
+      self.assertGreater(transport_multipliers.chi_e_multiplier, 1.0)
+
+
+if __name__ == '__main__':
+  absltest.main()