diff --git a/sklearn/base.py b/sklearn/base.py
index 0bd9327c38166..3ef2a908cdadf 100644
--- a/sklearn/base.py
+++ b/sklearn/base.py
@@ -417,8 +417,7 @@ def _check_feature_names(self, X, *, reset):
             fitted_feature_names != X_feature_names
         ):
             message = (
-                "The feature names should match those that were "
-                "passed during fit. Starting version 1.2, an error will be raised.\n"
+                "The feature names should match those that were passed during fit.\n"
             )
             fitted_feature_names_set = set(fitted_feature_names)
             X_feature_names_set = set(X_feature_names)
@@ -449,7 +448,7 @@ def add_names(names):
                     "Feature names must be in the same order as they were in fit.\n"
                 )
 
-            warnings.warn(message, FutureWarning)
+            raise ValueError(message)
 
     def _validate_data(
         self,
diff --git a/sklearn/tests/test_base.py b/sklearn/tests/test_base.py
index 6e17721046e9b..934bf7719163c 100644
--- a/sklearn/tests/test_base.py
+++ b/sklearn/tests/test_base.py
@@ -615,7 +615,7 @@ def transform(self, X):
     trans.fit(df)
     msg = "The feature names should match those that were passed"
     df_bad = pd.DataFrame(X_np, columns=iris.feature_names[::-1])
-    with pytest.warns(FutureWarning, match=msg):
+    with pytest.raises(ValueError, match=msg):
         trans.transform(df_bad)
 
     # warns when fitted on dataframe and transforming a ndarray
diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py
index 90efa06073487..8a1f4eb95583a 100644
--- a/sklearn/utils/estimator_checks.py
+++ b/sklearn/utils/estimator_checks.py
@@ -3913,22 +3913,14 @@ def check_dataframe_column_names_consistency(name, estimator_orig):
         X_bad = pd.DataFrame(X, columns=invalid_name)
 
         expected_msg = re.escape(
-            "The feature names should match those that were passed "
-            "during fit. Starting version 1.2, an error will be raised.\n"
+            "The feature names should match those that were passed during fit.\n"
             f"{additional_message}"
         )
         for name, method in check_methods:
-            # TODO In 1.2, this will be an error.
-            with warnings.catch_warnings():
-                warnings.filterwarnings(
-                    "error",
-                    category=FutureWarning,
-                    module="sklearn",
-                )
-                with raises(
-                    FutureWarning, match=expected_msg, err_msg=f"{name} did not raise"
-                ):
-                    method(X_bad)
+            with raises(
+                ValueError, match=expected_msg, err_msg=f"{name} did not raise"
+            ):
+                method(X_bad)
 
         # partial_fit checks on second call
         # Do not call partial fit if early_stopping is on
@@ -3942,10 +3934,8 @@ def check_dataframe_column_names_consistency(name, estimator_orig):
         else:
             estimator.partial_fit(X, y)
 
-        with warnings.catch_warnings():
-            warnings.filterwarnings("error", category=FutureWarning, module="sklearn")
-            with raises(FutureWarning, match=expected_msg):
-                estimator.partial_fit(X_bad, y)
+        with raises(ValueError, match=expected_msg):
+            estimator.partial_fit(X_bad, y)
 
 
 def check_transformer_get_feature_names_out(name, transformer_orig):