The advanced design of bioleaching process for metal recovery: A machine learning approach

•Estimation of recovery rate in bioleaching processes by a machine learning approach.•Using different ML algorithms to find the most efficient model for recovery rate estimation.•Optimization of a Random Forest model to minimize the estimation error.•Evaluation of the frequency distribution of input variables in the bioleaching studies.•Determining the order of the importance of input variables for estimation of the recovery rate.