diff --git a/lindi/LindiH5Store/_zarr_info_for_h5_dataset.py b/lindi/LindiH5Store/_zarr_info_for_h5_dataset.py
index 9b32407..568079d 100644
--- a/lindi/LindiH5Store/_zarr_info_for_h5_dataset.py
+++ b/lindi/LindiH5Store/_zarr_info_for_h5_dataset.py
@@ -88,8 +88,8 @@ def _zarr_info_for_h5_dataset(h5_dataset: h5py.Dataset) -> ZarrInfoForH5Dataset:
             raise Exception(f'Cannot handle scalar dataset {h5_dataset.name} with dtype {dtype}')
     else:
         # not a scalar dataset
-        if dtype.kind in ['i', 'u', 'f']:  # integer, unsigned integer, float
-            # This is the normal case of a chunked dataset with a numeric dtype
+        if dtype.kind in ['i', 'u', 'f', 'b']:  # integer, unsigned integer, float, boolean
+            # This is the normal case of a chunked dataset with a numeric (or boolean) dtype
             filters = _h5_filters_to_codecs(h5_dataset)
             chunks = h5_dataset.chunks
             if chunks is None:
diff --git a/tests/test_core.py b/tests/test_core.py
index 40bfa5a..ca4fb86 100644
--- a/tests/test_core.py
+++ b/tests/test_core.py
@@ -39,9 +39,10 @@ def test_scalar_datasets():
 
 
 def test_numpy_arrays():
-    X1 = ("1", np.arange(60).reshape(3, 20), (3, 7))
-    X2 = ("2", np.arange(60).reshape(3, 20), None)
-    for label, array, chunks in [X1, X2]:
+    array_1 = ("1", np.arange(60).reshape(3, 20), (3, 7))
+    array_2 = ("2", np.arange(60).reshape(3, 20), None)
+    array_boolean = ("3", np.array([[True, False, True], [False, True, False]]), None)
+    for label, array, chunks in [array_1, array_2, array_boolean]:
         print(f"Testing numpy array {label}")
         with tempfile.TemporaryDirectory() as tmpdir:
             filename = f"{tmpdir}/test.h5"