diff --git a/stubs/sklearn/_typing.pyi b/stubs/sklearn/_typing.pyi
index 33a33acb..0ff1251c 100644
--- a/stubs/sklearn/_typing.pyi
+++ b/stubs/sklearn/_typing.pyi
@@ -5,8 +5,10 @@
 import io
 import typing_extensions
 from decimal import Decimal as Decimal
+from typing import Any
 
 import numpy as np
+import numpy.typing as npt
 import pandas as pd
 from numpy.typing import ArrayLike as ArrayLike
 from scipy.sparse import spmatrix
@@ -15,7 +17,8 @@ from .base import BaseEstimator, ClassifierMixin, RegressorMixin
 
 PythonScalar: typing_extensions.TypeAlias = str | int | float | bool
 
-MatrixLike: typing_extensions.TypeAlias = np.ndarray | pd.DataFrame | spmatrix
+NDArray: typing_extensions.TypeAlias = npt.NDArray[Any]
+MatrixLike: typing_extensions.TypeAlias = NDArray | pd.DataFrame | spmatrix
 FileLike = io.IOBase
 PathLike = str
 Int: typing_extensions.TypeAlias = int | np.int8 | np.int16 | np.int32 | np.int64
diff --git a/stubs/sklearn/linear_model/_base.pyi b/stubs/sklearn/linear_model/_base.pyi
index 08ede4c0..d4029172 100644
--- a/stubs/sklearn/linear_model/_base.pyi
+++ b/stubs/sklearn/linear_model/_base.pyi
@@ -2,10 +2,9 @@ from abc import ABCMeta, abstractmethod
 from typing import ClassVar
 from typing_extensions import Self
 
-from numpy import ndarray
 from numpy.random.mtrand import RandomState
 
-from .._typing import ArrayLike, Int, MatrixLike
+from .._typing import ArrayLike, Int, MatrixLike, NDArray
 from ..base import BaseEstimator as BaseEstimator, ClassifierMixin, MultiOutputMixin, RegressorMixin
 from ..utils._seq_dataset import ArrayDataset64, CSRDataset64
 from ._stochastic_gradient import SGDClassifier
@@ -22,23 +21,23 @@ def make_dataset(
 class LinearModel(BaseEstimator, metaclass=ABCMeta):
     @abstractmethod
     def fit(self, X, y): ...
-    def predict(self, X: MatrixLike) -> ndarray: ...
+    def predict(self, X: MatrixLike) -> NDArray: ...
 
 class LinearClassifierMixin(ClassifierMixin):
-    def decision_function(self, X: MatrixLike | ArrayLike) -> ndarray: ...
-    def predict(self, X: MatrixLike | ArrayLike) -> ndarray: ...
+    def decision_function(self, X: MatrixLike | ArrayLike) -> NDArray: ...
+    def predict(self, X: MatrixLike | ArrayLike) -> NDArray: ...
 
 class SparseCoefMixin:
     def densify(self) -> Self: ...
     def sparsify(self) -> SGDClassifier | Self: ...
 
 class LinearRegression(MultiOutputMixin, RegressorMixin, LinearModel):
-    feature_names_in_: ndarray = ...
+    feature_names_in_: NDArray = ...
     n_features_in_: int = ...
-    intercept_: float | ndarray = ...
-    singular_: ndarray = ...
+    intercept_: float | NDArray = ...
+    singular_: NDArray = ...
     rank_: int = ...
-    coef_: ndarray = ...
+    coef_: NDArray = ...
 
     _parameter_constraints: ClassVar[dict] = ...