diff --git a/python/pyarrow/array.pxi b/python/pyarrow/array.pxi
index f99af9853e518..e29136cc1aef0 100644
--- a/python/pyarrow/array.pxi
+++ b/python/pyarrow/array.pxi
@@ -491,7 +491,8 @@ cdef class _PandasConvertible:
             bint deduplicate_objects=True,
             bint ignore_metadata=False,
             bint split_blocks=False,
-            bint self_destruct=False
+            bint self_destruct=False,
+            types_mapping=None
     ):
         """
         Convert to a pandas-compatible NumPy array or DataFrame, as appropriate
@@ -531,6 +532,11 @@ cdef class _PandasConvertible:
             memory while converting the Arrow object to pandas. If you use the
             object after calling to_pandas with this option it will crash your
             program
+        types_mapping : dict, default None
+            A mapping from pyarrow DataType to pandas ExtensionDtype. This can
+            be used to override the default pandas type for conversion of
+            built-in pyarrow types or in absence of pandas_metadata in the
+            Table schema.
 
         Returns
         -------
@@ -548,7 +554,8 @@ cdef class _PandasConvertible:
             self_destruct=self_destruct
         )
         return self._to_pandas(options, categories=categories,
-                               ignore_metadata=ignore_metadata)
+                               ignore_metadata=ignore_metadata,
+                               types_mapping=types_mapping)
 
 
 cdef PandasOptions _convert_pandas_options(dict options):
diff --git a/python/pyarrow/pandas_compat.py b/python/pyarrow/pandas_compat.py
index bab12bf1de280..b986e84d0ca30 100644
--- a/python/pyarrow/pandas_compat.py
+++ b/python/pyarrow/pandas_compat.py
@@ -741,7 +741,8 @@ def make_datetimetz(tz):
 
 
 def table_to_blockmanager(options, table, categories=None,
-                          extension_columns=None, ignore_metadata=False):
+                          extension_columns=None, ignore_metadata=False,
+                          types_mapping=None):
     from pandas.core.internals import BlockManager
 
     all_columns = []
@@ -756,14 +757,14 @@ def table_to_blockmanager(options, table, categories=None,
         table, index = _reconstruct_index(table, index_descriptors,
                                           all_columns)
         ext_columns_dtypes = _get_extension_dtypes(
-            table, all_columns, extension_columns)
+            table, all_columns, extension_columns, types_mapping)
     else:
         index = _pandas_api.pd.RangeIndex(table.num_rows)
         if extension_columns:
             raise ValueError("extension_columns not supported if there is "
                              "no pandas_metadata")
         ext_columns_dtypes = _get_extension_dtypes(
-            table, [], extension_columns)
+            table, [], extension_columns, types_mapping)
 
     _check_data_column_metadata_consistency(all_columns)
     columns = _deserialize_column_index(table, all_columns, column_indexes)
@@ -782,7 +783,8 @@ def table_to_blockmanager(options, table, categories=None,
 ])
 
 
-def _get_extension_dtypes(table, columns_metadata, extension_columns):
+def _get_extension_dtypes(table, columns_metadata, extension_columns,
+                          types_mapping=None):
     """
     Based on the stored column pandas metadata and the extension types
     in the arrow schema, infer which columns should be converted to a
@@ -840,6 +842,12 @@ def _get_extension_dtypes(table, columns_metadata, extension_columns):
                                  "converted to extension dtype")
             ext_columns[name] = pandas_dtype
 
+    if types_mapping:
+        for field in table.schema:
+            typ = field.type
+            if typ in types_mapping:
+                ext_columns[field.name] = types_mapping[typ]
+
     return ext_columns
 
 
diff --git a/python/pyarrow/table.pxi b/python/pyarrow/table.pxi
index 1cd575e0c843d..4d7176d0c6a3b 100644
--- a/python/pyarrow/table.pxi
+++ b/python/pyarrow/table.pxi
@@ -1361,11 +1361,13 @@ cdef class Table(_PandasConvertible):
 
         return result
 
-    def _to_pandas(self, options, categories=None, ignore_metadata=False):
+    def _to_pandas(self, options, categories=None, ignore_metadata=False,
+                   types_mapping=None):
         from pyarrow.pandas_compat import table_to_blockmanager
         mgr = table_to_blockmanager(
             options, self, categories,
-            ignore_metadata=ignore_metadata)
+            ignore_metadata=ignore_metadata,
+            types_mapping=types_mapping)
         return pandas_api.data_frame(mgr)
 
     def to_pydict(self):
diff --git a/python/pyarrow/tests/test_pandas.py b/python/pyarrow/tests/test_pandas.py
index 61d09e2b20baf..af12c6bd2b4a9 100644
--- a/python/pyarrow/tests/test_pandas.py
+++ b/python/pyarrow/tests/test_pandas.py
@@ -3544,6 +3544,21 @@ def test_conversion_extensiontype_to_extensionarray(monkeypatch):
         table.to_pandas()
 
 
+def test_to_pandas_extension_dtypes_mapping():
+    if LooseVersion(pd.__version__) < "0.26.0.dev":
+        pytest.skip("Conversion to pandas IntegerArray not yet supported")
+
+    table = pa.table({'a': pa.array([1, 2, 3], pa.int64())})
+
+    # default use numpy dtype
+    result = table.to_pandas()
+    assert result['a'].dtype == np.dtype('int64')
+
+    # specify to override the default
+    result = table.to_pandas(types_mapping={pa.int64(): pd.Int64Dtype()})
+    assert isinstance(result['a'].dtype, pd.Int64Dtype)
+
+
 # ----------------------------------------------------------------------
 # Legacy metadata compatibility tests