diff --git a/doc/source/whatsnew/v1.5.0.rst b/doc/source/whatsnew/v1.5.0.rst
index 50a5bf383de77..17070b06a47d0 100644
--- a/doc/source/whatsnew/v1.5.0.rst
+++ b/doc/source/whatsnew/v1.5.0.rst
@@ -535,6 +535,7 @@ Reshaping
 - Bug in :func:`get_dummies` that selected object and categorical dtypes but not string (:issue:`44965`)
 - Bug in :meth:`DataFrame.align` when aligning a :class:`MultiIndex` to a :class:`Series` with another :class:`MultiIndex` (:issue:`46001`)
 - Bug in concanenation with ``IntegerDtype``, or ``FloatingDtype`` arrays where the resulting dtype did not mirror the behavior of the non-nullable dtypes (:issue:`46379`)
+- Bug in :func:`concat` between two :class:`DataFrame` with categorical indexes that have the same categories returning with indexes in improper order (:issue:`44099`)
 -
 
 Sparse
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index c2bcd90ff10fb..1b0a453ec41c8 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -571,7 +571,10 @@ def map(self, mapper):
     def _concat(self, to_concat: list[Index], name: Hashable) -> Index:
         # if calling index is category, don't check dtype of others
         try:
-            codes = np.concatenate([self._is_dtype_compat(c).codes for c in to_concat])
+            data = np.concatenate(
+                [self._is_dtype_compat(c).tolist() for c in to_concat]
+            )
+            codes = Categorical(data, categories=self.categories).codes
         except TypeError:
             # not all to_concat elements are among our categories (or NA)
             from pandas.core.dtypes.concat import concat_compat
diff --git a/pandas/tests/indexes/categorical/test_category.py b/pandas/tests/indexes/categorical/test_category.py
index 06c00123566ba..fea859a4e3da9 100644
--- a/pandas/tests/indexes/categorical/test_category.py
+++ b/pandas/tests/indexes/categorical/test_category.py
@@ -286,6 +286,18 @@ def test_map_str(self):
         # See test_map.py
         pass
 
+    def test_append(self):
+        # GH 44099
+        # concat indexes which have the same categories
+
+        ci1 = CategoricalIndex(["a", "b", "c"], categories=["a", "b", "c"])
+        ci2 = CategoricalIndex(["b", "a", "c"], categories=["b", "a", "c"])
+        expected = CategoricalIndex(
+            ["a", "b", "c", "b", "a", "c"], categories=["a", "b", "c"]
+        )
+        result = ci1.append(ci2)
+        tm.assert_index_equal(result, expected)
+
 
 class TestCategoricalIndex2:
     # Tests that are not overriding a test in Base
diff --git a/pandas/tests/reshape/concat/test_concat.py b/pandas/tests/reshape/concat/test_concat.py
index eb44b4889afb8..ef20f9f4b150c 100644
--- a/pandas/tests/reshape/concat/test_concat.py
+++ b/pandas/tests/reshape/concat/test_concat.py
@@ -18,6 +18,7 @@
 
 import pandas as pd
 from pandas import (
+    CategoricalIndex,
     DataFrame,
     Index,
     MultiIndex,
@@ -502,6 +503,27 @@ def test_concat_duplicate_indices_raise(self):
         with pytest.raises(InvalidIndexError, match=msg):
             concat([df1, df2], axis=1)
 
+    def test_concat_with_categorical_indices(self):
+        # GH 44099
+        # concat frames with categorical indices that have the same values
+
+        df1 = DataFrame(
+            {"col1": ["a_val", "b_val", "c_val"]},
+            index=CategoricalIndex(["a", "b", "c"], categories=["a", "b", "c"]),
+        )
+        df2 = DataFrame(
+            {"col1": ["b_val", "a_val", "c_val"]},
+            index=CategoricalIndex(["b", "a", "c"], categories=["b", "a", "c"]),
+        )
+        expected = DataFrame(
+            {"col1": ["a_val", "b_val", "c_val", "b_val", "a_val", "c_val"]},
+            index=CategoricalIndex(
+                ["a", "b", "c", "b", "a", "c"], categories=["a", "b", "c"]
+            ),
+        )
+        result = concat([df1, df2])
+        tm.assert_frame_equal(result, expected)
+
 
 @pytest.mark.parametrize("pdt", [Series, DataFrame])
 @pytest.mark.parametrize("dt", np.sctypes["float"])