diff --git a/src/everest/config/objective_function_config.py b/src/everest/config/objective_function_config.py
index 72f75c2551b..6f9f4453c8e 100644
--- a/src/everest/config/objective_function_config.py
+++ b/src/everest/config/objective_function_config.py
@@ -1,4 +1,8 @@
-from pydantic import BaseModel, Field, PositiveFloat, field_validator
+from typing import Self
+
+from pydantic import BaseModel, Field, PositiveFloat, field_validator, model_validator
+
+from ert.config.parsing import ConfigWarning
 
 
 class ObjectiveFunctionConfig(BaseModel, extra="forbid"):  # type: ignore
@@ -29,18 +33,30 @@ class ObjectiveFunctionConfig(BaseModel, extra="forbid"):  # type: ignore
     normalization: float | None = Field(
         default=None,
         description="""
-normalization is a multiplication factor defined per objective function.
-
-The value of each objective function is multiplied by the related normalization value.
-When optimizing with respect to multiple objective functions, it is important
-that the normalization is set so that all the normalized objectives have the same order
-of magnitude. Ultimately, the normalized objectives are used in computing
-the weighted sum that Everest tries to optimize.
+    normalization key is deprecated and has been replaced with scaling
 """,
+    )
+    scaling: float | None = Field(
+        default=None,
+        description="""
+    scaling is a multiplication factor defined per objective function.
+
+    The value of each objective function is multiplied by the related scaling value.
+    When optimizing with respect to multiple objective functions, it is important
+    that the scaling is set so that all the scaled objectives have the same order
+    of magnitude. Ultimately, the scaled objectives are used in computing
+    the weighted sum that Everest tries to optimize.
+    """,
     )
     auto_normalize: bool | None = Field(
         default=None,
         description="""
+    auto_normalize key is deprecated has been replaced with auto_scale.
+    """,
+    )
+    auto_scale: bool | None = Field(
+        default=None,
+        description="""
 auto_normalize can be set to true to automatically
 determine the normalization factor from the objective value in batch 0.
 
@@ -61,9 +77,31 @@ class ObjectiveFunctionConfig(BaseModel, extra="forbid"):  # type: ignore
 """,
     )
 
-    @field_validator("normalization")
+    @field_validator("scaling")
     @classmethod
-    def validate_normalization_is_not_zero(cls, normalization):  # pylint: disable=E0213
-        if normalization == 0.0:
+    def validate_scaling_is_not_zero(cls, scaling) -> float | None:
+        if scaling == 0.0:
             raise ValueError("Normalization value cannot be zero")
-        return normalization
+        return scaling
+
+    @model_validator(mode="after")
+    def deprecate_normalization(self) -> Self:
+        if self.normalization is not None:
+            ConfigWarning.deprecation_warn(
+                "normalization key is deprecated and has been replaced with scaling"
+            )
+        if self.auto_normalize is not None:
+            ConfigWarning.deprecation_warn(
+                "auto_normalize key is deprecated and has been replaced with auto_scale"
+            )
+        return self
+
+    @model_validator(mode="after")
+    def make_scaling_backwards_compatible(self) -> Self:
+        if self.scaling is None and self.normalization is not None:
+            self.scaling = self.normalization
+            if self.scaling == 0.0:
+                raise ValueError("Scaling value cannot be zero")
+        if self.auto_scale is None and self.auto_normalize is not None:
+            self.auto_scale = self.auto_normalize
+        return self
diff --git a/src/everest/everest_storage.py b/src/everest/everest_storage.py
index d762f5491ef..dd67110f3b8 100644
--- a/src/everest/everest_storage.py
+++ b/src/everest/everest_storage.py
@@ -424,7 +424,7 @@ def init(self, everest_config: EverestConfig) -> None:
                 "weight": pl.Series(weights / sum(weights), dtype=pl.Float64),
                 "normalization": pl.Series(
                     [
-                        1.0 if obj.normalization is None else obj.normalization
+                        1.0 if obj.scaling is None else obj.scaling
                         for obj in everest_config.objective_functions
                     ],
                     dtype=pl.Float64,
diff --git a/src/everest/optimizer/everest2ropt.py b/src/everest/optimizer/everest2ropt.py
index 20930704170..71b6b6c1e22 100644
--- a/src/everest/optimizer/everest2ropt.py
+++ b/src/everest/optimizer/everest2ropt.py
@@ -68,8 +68,8 @@ def _parse_objectives(objective_functions: list[ObjectiveFunctionConfig], ropt_c
     for objective in objective_functions:
         assert isinstance(objective.name, str)
         weights.append(objective.weight or 1.0)
-        scales.append(1.0 / (objective.normalization or 1.0))
-        auto_scale.append(objective.auto_normalize or False)
+        scales.append(1.0 / (objective.scaling or 1.0))
+        auto_scale.append(objective.auto_scale or False)
 
         # If any objective specifies an objective type, we have to specify
         # function estimators in ropt to implement these types. This is done by
diff --git a/tests/everest/test_config_validation.py b/tests/everest/test_config_validation.py
index f70c3650956..82a5f85e9ee 100644
--- a/tests/everest/test_config_validation.py
+++ b/tests/everest/test_config_validation.py
@@ -13,7 +13,7 @@
 
 from ert.config import ConfigWarning
 from ert.config.parsing import ConfigValidationError
-from everest.config import EverestConfig, ModelConfig
+from everest.config import EverestConfig, ModelConfig, ObjectiveFunctionConfig
 from everest.config.control_variable_config import ControlVariableConfig
 from everest.config.sampler_config import SamplerConfig
 from everest.simulator.everest_to_ert import everest_to_ert_config
@@ -1068,3 +1068,54 @@ def test_warning_empty_controls_and_objectives(controls, objectives, error_msg):
             objective_functions=objectives,
             controls=controls,
         )
+
+
+def test_deprecated_objective_function_normalization():
+    with pytest.warns(
+        ConfigWarning, match="normalization key is deprecated .* replaced with scaling"
+    ):
+        ObjectiveFunctionConfig(name="test", normalization=10)
+
+
+def test_deprecated_objective_function_auto_normalize():
+    with pytest.warns(
+        ConfigWarning,
+        match="auto_normalize key is deprecated .* replaced with auto_scale",
+    ):
+        ObjectiveFunctionConfig(name="test", auto_normalize=True)
+
+
+@pytest.mark.parametrize(
+    "normalization, scaling, auto_normalize, auto_scale",
+    [
+        (None, None, None, None),
+        (0.2, None, None, None),
+        (0.42, 0.24, None, None),
+        (None, 0.24, None, None),
+        (None, None, True, None),
+        (None, None, True, False),
+        (None, None, None, False),
+        (0.42, 0.24, True, False),
+    ],
+)
+def test_objective_function_scaling_is_backward_compatible_with_scaling(
+    normalization, auto_normalize, scaling, auto_scale
+):
+    o = ObjectiveFunctionConfig(
+        name="test",
+        normalization=normalization,
+        auto_normalize=auto_normalize,
+        scaling=scaling,
+        auto_scale=auto_scale,
+    )
+    if scaling is None and normalization is not None:
+        assert o.scaling == o.normalization
+    else:
+        assert o.scaling == scaling
+        assert o.normalization == normalization
+
+    if auto_scale is None and auto_normalize is not None:
+        assert o.auto_scale == o.auto_normalize
+    else:
+        assert o.auto_scale == auto_scale
+        assert o.auto_normalize == auto_normalize