diff --git a/etl/epc/tests/test_epcrecord.py b/etl/epc/tests/test_epcrecord.py
index 9dc2c01b..30076711 100644
--- a/etl/epc/tests/test_epcrecord.py
+++ b/etl/epc/tests/test_epcrecord.py
@@ -309,3 +309,88 @@ class TestEpcRecord:
         base_record._apply_cleaning_rules()
 
         assert base_record._prepared_epc["extension-count"] == 2
+
+    def test_apply_averages_cleaning_fills_missing_values(self, cleaning_data):
+        record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
+
+        record._prepared_epc = {
+            "property-type": cleaning_data["property_type"].iloc[0],
+            "local-authority": cleaning_data["local_authority"].iloc[0],
+            "total-floor-area": float(cleaning_data["total_floor_area"].iloc[0]),
+
+            "number-habitable-rooms": None,
+            "number-heated-rooms": None,
+            "floor-height": None,
+        }
+
+        record._apply_averages_cleaning()
+
+        assert record._prepared_epc["number-habitable-rooms"] is not None
+        assert record._prepared_epc["number-heated-rooms"] is not None
+        assert record._prepared_epc["floor-height"] is not None
+
+    def test_apply_averages_cleaning_no_missing(self, cleaning_data):
+        record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
+
+        record._prepared_epc = {
+            "property-type": cleaning_data["property_type"].iloc[0],
+            "local-authority": cleaning_data["local_authority"].iloc[0],
+            "total-floor-area": float(cleaning_data["total_floor_area"].iloc[0]),
+
+            "number-habitable-rooms": 5,
+            "number-heated-rooms": 5,
+            "floor-height": 2.5,
+        }
+
+        original = record._prepared_epc.copy()
+
+        record._apply_averages_cleaning()
+
+        assert record._prepared_epc == original
+
+    def test_apply_averages_cleaning_caps_heated_rooms(self, cleaning_data):
+        record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
+
+        record._prepared_epc = {
+            "property-type": cleaning_data["property_type"].iloc[0],
+            "local-authority": cleaning_data["local_authority"].iloc[0],
+            "total-floor-area": float(cleaning_data["total_floor_area"].iloc[0]),
+
+            "number-habitable-rooms": None,
+            "number-heated-rooms": None,
+            "floor-height": None,
+        }
+
+        record._apply_averages_cleaning()
+
+        assert (
+            record._prepared_epc["number-heated-rooms"]
+            <= record._prepared_epc["number-habitable-rooms"]
+        )
+
+    def test_apply_averages_cleaning_floor_area_filter(self, cleaning_data):
+        record = EPCRecord(run_mode="training", cleaning_data=cleaning_data)
+
+        floor_area = float(cleaning_data["total_floor_area"].median())
+
+        record._prepared_epc = {
+            "property-type": cleaning_data["property_type"].iloc[0],
+            "local-authority": cleaning_data["local_authority"].iloc[0],
+            "total-floor-area": floor_area,
+
+            "number-habitable-rooms": None,
+            "number-heated-rooms": None,
+            "floor-height": None,
+        }
+
+        record._apply_averages_cleaning()
+
+        assert record._prepared_epc["floor-height"] > 0
+
+    def test_apply_averages_cleaning_requires_cleaning_data(self):
+        record = EPCRecord(run_mode="training", cleaning_data=None)
+
+        record._prepared_epc = {}
+
+        with pytest.raises(ValueError):
+            record._apply_averages_cleaning()