diff --git a/modin/core/storage_formats/base/query_compiler.py b/modin/core/storage_formats/base/query_compiler.py
index 76d3902a6e3..dc7f2fce17b 100644
--- a/modin/core/storage_formats/base/query_compiler.py
+++ b/modin/core/storage_formats/base/query_compiler.py
@@ -1956,7 +1956,7 @@ def searchsorted(self, **kwargs):  # noqa: PR02
     # END Abstract map partitions operations
 
     @doc_utils.add_refer_to("DataFrame.stack")
-    def stack(self, level, dropna):
+    def stack(self, level, dropna, sort):
         """
         Stack the prescribed level(s) from columns to index.
 
@@ -1964,13 +1964,17 @@ def stack(self, level, dropna):
         ----------
         level : int or label
         dropna : bool
+        sort : bool
 
         Returns
         -------
         BaseQueryCompiler
         """
         return DataFrameDefault.register(pandas.DataFrame.stack)(
-            self, level=level, dropna=dropna
+            self,
+            level=level,
+            dropna=dropna,
+            sort=sort,
         )
 
     # Abstract map partitions across select indices
diff --git a/modin/core/storage_formats/pandas/query_compiler.py b/modin/core/storage_formats/pandas/query_compiler.py
index cd0e59ca56f..b62f2aa4474 100644
--- a/modin/core/storage_formats/pandas/query_compiler.py
+++ b/modin/core/storage_formats/pandas/query_compiler.py
@@ -1962,7 +1962,7 @@ def get_unique_level_values(index):
             result = result.reindex(0, new_index)
         return result
 
-    def stack(self, level, dropna):
+    def stack(self, level, dropna, sort):
         if not isinstance(self.columns, pandas.MultiIndex) or (
             isinstance(self.columns, pandas.MultiIndex)
             and is_list_like(level)
@@ -1974,7 +1974,9 @@ def stack(self, level, dropna):
 
         new_modin_frame = self._modin_frame.apply_full_axis(
             1,
-            lambda df: pandas.DataFrame(df.stack(level=level, dropna=dropna)),
+            lambda df: pandas.DataFrame(
+                df.stack(level=level, dropna=dropna, sort=sort)
+            ),
             new_columns=new_columns,
         )
         return self.__constructor__(new_modin_frame)
diff --git a/modin/pandas/dataframe.py b/modin/pandas/dataframe.py
index e90837a3b6d..4f47c9374e9 100644
--- a/modin/pandas/dataframe.py
+++ b/modin/pandas/dataframe.py
@@ -2118,11 +2118,11 @@ def stack(
             is_multiindex and is_list_like(level) and len(level) == self.columns.nlevels
         ):
             return self._reduce_dimension(
-                query_compiler=self._query_compiler.stack(level, dropna)
+                query_compiler=self._query_compiler.stack(level, dropna, sort)
             )
         else:
             return self.__constructor__(
-                query_compiler=self._query_compiler.stack(level, dropna)
+                query_compiler=self._query_compiler.stack(level, dropna, sort)
             )
 
     def sub(
diff --git a/modin/tests/pandas/dataframe/test_default.py b/modin/tests/pandas/dataframe/test_default.py
index 71f49924c94..d40a30e38e9 100644
--- a/modin/tests/pandas/dataframe/test_default.py
+++ b/modin/tests/pandas/dataframe/test_default.py
@@ -1181,6 +1181,16 @@ def test_stack(data, is_multi_idx, is_multi_col):
         df_equals(modin_df.stack(level=[0, 1, 2]), pandas_df.stack(level=[0, 1, 2]))
 
 
+@pytest.mark.parametrize("sort", [True, False])
+def test_stack_sort(sort):
+    # Example frame slightly modified from pandas docs to be unsorted
+    cols = pd.MultiIndex.from_tuples([("weight", "pounds"), ("weight", "kg")])
+    modin_df, pandas_df = create_test_dfs(
+        [[1, 2], [2, 4]], index=["cat", "dog"], columns=cols
+    )
+    df_equals(modin_df.stack(sort=sort), pandas_df.stack(sort=sort))
+
+
 @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
 @pytest.mark.parametrize("axis1", [0, 1])
 @pytest.mark.parametrize("axis2", [0, 1])