Following model development, we evaluate their performance by examining residuals and using local regression (loess). The results indicate no significant bias in the predictions relative to the magnitude of predicted values. Furthermore, we conduct a 5-fold Cross Validation and evaluate the same model evaluation metrics, which yield similar results. This robust performance suggests that our RFR models effectively capture the complex relationships between predictor variables (such as total AADT, roadway classification, and lane configurations) and MDV and HDV traffic volumes, while minimizing prediction errors.