diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst
index 0760840f9950a..d703c38d30063 100644
--- a/doc/source/whatsnew/v2.2.0.rst
+++ b/doc/source/whatsnew/v2.2.0.rst
@@ -248,6 +248,7 @@ Performance improvements
 Bug fixes
 ~~~~~~~~~
 - Bug in :class:`AbstractHolidayCalendar` where timezone data was not propagated when computing holiday observances (:issue:`54580`)
+- Bug in :class:`pandas.core.window.Rolling` where df.rolling does not work with 'datetime64[us]', 'datetime64[ms]', and 'datetime64[s]' index types (:issue:`55299`)
 - Bug in :class:`pandas.core.window.Rolling` where duplicate datetimelike indexes are treated as consecutive rather than equal with ``closed='left'`` and ``closed='neither'`` (:issue:`20712`)
 - Bug in :meth:`DataFrame.apply` where passing ``raw=True`` ignored ``args`` passed to the applied function (:issue:`55009`)
 - Bug in :meth:`pandas.read_excel` with a ODS file without cached formatted cell for float values (:issue:`55219`)
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 72e94d049a9de..99d46bc09be0f 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -405,6 +405,8 @@ def _index_array(self):
         # TODO: why do we get here with e.g. MultiIndex?
         if needs_i8_conversion(self._on.dtype):
             idx = cast("PeriodIndex | DatetimeIndex | TimedeltaIndex", self._on)
+            if (type(idx) == DatetimeIndex) and (idx.T.unit != "ns"):
+                idx = idx.astype("datetime64[ns]")
             return idx.asi8
         return None
 
diff --git a/pandas/tests/window/test_rolling.py b/pandas/tests/window/test_rolling.py
index 3fe922539780d..03ff6bee49a37 100644
--- a/pandas/tests/window/test_rolling.py
+++ b/pandas/tests/window/test_rolling.py
@@ -1950,3 +1950,30 @@ def test_numeric_only_corr_cov_series(kernel, use_arg, numeric_only, dtype):
         op2 = getattr(rolling2, kernel)
         expected = op2(*arg2, numeric_only=numeric_only)
         tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "data_type",
+    [
+        "datetime64[us]",
+        "datetime64[ms]",
+        "datetime64[s]",
+    ],
+)
+def test_rolling_sum_on_dtypes(data_type):
+    # GH 55299
+    index = [
+        "2019-01-03 05:11",
+        "2019-01-03 05:23",
+        "2019-01-03 05:28",
+        "2019-01-03 05:32",
+        "2019-01-03 05:36",
+    ]
+    arr = [True, False, False, True, True]
+
+    df_exp = DataFrame({"arr": arr}, index=to_datetime(index).astype("datetime64[ns]"))
+    df_test = DataFrame({"arr": arr}, index=to_datetime(index).astype(data_type))
+    sum_df_exp = df_exp.rolling("5min").sum()
+    sum_df_test = df_test.rolling("5min").sum()
+
+    assert list(sum_df_test.values) == list(sum_df_exp.values)