diff --git a/nannyml/sampling_error/binary_classification.py b/nannyml/sampling_error/binary_classification.py
index e8232ce9..bcd4a0f6 100644
--- a/nannyml/sampling_error/binary_classification.py
+++ b/nannyml/sampling_error/binary_classification.py
@@ -178,6 +178,10 @@ def f1_sampling_error_components(y_true_reference: pd.Series, y_pred_reference:
 
     tp_fp_fn = np.concatenate([TP, FN, FP])
 
+    # If there's no true positives, false negatives or false positives, sampling error is NaN
+    if tp_fp_fn.size == 0:
+        return np.nan, 0
+
     correcting_factor = len(tp_fp_fn) / ((len(FN) + len(FP)) * 0.5 + len(TP))
     obs_level_f1 = tp_fp_fn * correcting_factor
     fraction_of_relevant = len(tp_fp_fn) / len(y_pred_reference)