On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development

•Machine learning (ML) model interpretability is critical for safety data modeling.•ML model interpretation methods are reviewed and compared.•It is feasible to use ML and SHAP to derive crash modification factors.•It is important to differentiate causation from correlation in ML safety studies.