diff --git a/tests/performance_estimation/CBPE/test_cbpe_metrics.py b/tests/performance_estimation/CBPE/test_cbpe_metrics.py
index d1e42c2e..c2ae06cb 100644
--- a/tests/performance_estimation/CBPE/test_cbpe_metrics.py
+++ b/tests/performance_estimation/CBPE/test_cbpe_metrics.py
@@ -3473,6 +3473,12 @@ def test_method_logs_warning_when_lower_threshold_is_overridden_by_metric_limits
             pd.DataFrame(
                 {
                     'key': ['[0:19999]', '[20000:39999]', '[40000:59999]'],
+                    'realized_roc_auc': [0.909805, 0.840071, np.nan],
+                    'realized_f1': [0.759170, 0.658896, np.nan],
+                    'realized_precision': [0.759265, 0.660188, np.nan],
+                    'realized_recall': [0.759149, 0.658760, np.nan],
+                    'realized_specificity': [0.879632, 0.829581, np.nan],
+                    'realized_accuracy': [0.75925, 0.65950, np.nan],
                     'realized_true_highstreet_card_pred_highstreet_card': [
                         4912.0,
                         4702.0,
@@ -3523,7 +3529,7 @@ def test_method_logs_warning_when_lower_threshold_is_overridden_by_metric_limits
         ),
     ]
 )
-def test_cbpe_for_multiclass_classification_cm_with_nans(calculator_opts, estimated, realized):  # noqa: D103
+def test_cbpe_for_multiclass_classification_cm_with_nans(calculator_opts, realized):  # noqa: D103
     """Test Nan Handling of CM MC metric."""
     reference, analysis, targets = load_synthetic_multiclass_classification_dataset()
     analysis = analysis.merge(targets, left_index=True, right_index=True)
@@ -3537,11 +3543,13 @@ def test_cbpe_for_multiclass_classification_cm_with_nans(calculator_opts, estima
         y_pred='y_pred',
         y_true='y_true',
         problem_type='classification_multiclass',
-        metrics=['confusion_matrix'],
+        metrics=['roc_auc', 'f1', 'precision', 'recall', 'specificity', 'accuracy', 'confusion_matrix'],
         **calculator_opts,
     ).fit(reference)
     result = cbpe.estimate(analysis)
-    column_names = [
+    column_names = [(m.name, 'realized') for m in result.metrics]
+    column_names = [c for c in column_names if c[0] != 'confusion_matrix']
+    column_names += [
         ('true_highstreet_card_pred_highstreet_card', 'realized'),
         ('true_highstreet_card_pred_prepaid_card', 'realized'),
         ('true_highstreet_card_pred_upmarket_card', 'realized'),
@@ -3555,6 +3563,12 @@ def test_cbpe_for_multiclass_classification_cm_with_nans(calculator_opts, estima
     sut = result.filter(period='analysis').to_df()[[('chunk', 'key')] + column_names]
     sut.columns = [
         'key',
+        'realized_roc_auc',
+        'realized_f1',
+        'realized_precision',
+        'realized_recall',
+        'realized_specificity',
+        'realized_accuracy',
         'realized_true_highstreet_card_pred_highstreet_card',
         'realized_true_highstreet_card_pred_prepaid_card',
         'realized_true_highstreet_card_pred_upmarket_card',