diff --git a/doc/source/whatsnew/v1.0.0.rst b/doc/source/whatsnew/v1.0.0.rst
index cde2a4279cf27..c95e7d20c1ab4 100644
--- a/doc/source/whatsnew/v1.0.0.rst
+++ b/doc/source/whatsnew/v1.0.0.rst
@@ -223,7 +223,7 @@ Categorical
 - Bug where :func:`merge` was unable to join on categorical and extension dtype columns (:issue:`28668`)
 - :meth:`Categorical.searchsorted` and :meth:`CategoricalIndex.searchsorted` now work on unordered categoricals also (:issue:`21667`)
 - Added test to assert roundtripping to parquet with :func:`DataFrame.to_parquet` or :func:`read_parquet` will preserve Categorical dtypes for string types (:issue:`27955`)
--
+- Bug in merge on CategoricalIndex fails if ``left_index=True`` & ``right_index=True``, but not if ``on={index}`` (:issue:`28189`)-
 
 
 Datetimelike
diff --git a/pandas/_libs/join.pyx b/pandas/_libs/join.pyx
index 238bfd0be0aa7..12d6439ed5b17 100644
--- a/pandas/_libs/join.pyx
+++ b/pandas/_libs/join.pyx
@@ -242,6 +242,8 @@ ctypedef fused join_t:
     float64_t
     float32_t
     object
+    int8_t
+    int16_t
     int32_t
     int64_t
     uint64_t
@@ -410,6 +412,11 @@ def left_join_indexer(ndarray[join_t] left, ndarray[join_t] right):
 left_join_indexer_float64 = left_join_indexer["float64_t"]
 left_join_indexer_float32 = left_join_indexer["float32_t"]
 left_join_indexer_object = left_join_indexer["object"]
+left_join_indexer_int8 = left_join_indexer["int8_t"]
+<<<<<<< HEAD
+=======
+left_join_indexer_int16 = left_join_indexer["int16_t"]
+>>>>>>> 4e8bf1f62a82e6fec532c91297b0b5a908351c3d
 left_join_indexer_int32 = left_join_indexer["int32_t"]
 left_join_indexer_int64 = left_join_indexer["int64_t"]
 left_join_indexer_uint64 = left_join_indexer["uint64_t"]
diff --git a/pandas/tests/test_join.py b/pandas/tests/test_join.py
index e750193abb71a..3f87317d77f27 100644
--- a/pandas/tests/test_join.py
+++ b/pandas/tests/test_join.py
@@ -348,3 +348,21 @@ def test_merge_join_categorical_multiindex():
     result = a.join(b, on=["Cat1", "Int1"])
     expected = expected.drop(["Cat", "Int"], axis=1)
     assert_frame_equal(expected, result)
+
+
+def test_left_index_and_right_index_true():
+    # From issue 28189
+    df = DataFrame(
+        range(4), columns=["value"], index=Index(Categorical(["1"] * 4), name="idx")
+    )
+    df2 = DataFrame(
+        [[6]], columns=["value"], index=Index(Categorical(["1"]), name="idx")
+    )
+
+    result = merge(df, df2, how="left", left_index=True, right_index=True)
+    result = result.reset_index(drop=True)
+    expected = DataFrame(
+        np.array([[0, 6], [1, 6], [2, 6], [3, 6]]), columns=["value_x", "value_y"]
+    )
+
+    assert_frame_equal(expected, result)