A comparative study of various machine learning methods for performance prediction of an evaporative condenser

•The performance of an evaporative condenser was studied via data-driven models.•A large experimental dataset (339 tests) compared to previous studies was employed.•The robustness of SVR, DT, and RF models compared to MLPANN was investigated.•Feature importance analysis was performed by the random forest model.•The effect of dataset size on the predictive performance of the models was studied.