Wastewater of mining industries contain high loads of heavy metals. Based on the important role of pH in chemical precipitation of heavy metals, the objective was to find the best pH for the highest amount of precipitation during pH adjustment with aeration for different concentrations (by dilution) and to model it with Artificial Neural Network (ANN). All of data gained from experiments were entered as inputs into a multi-layer perceptron (MLP) network. Experiments show that by increasing pH from acidic to neutral zone, all of parameters reach minimum amount in pH 7.5 and samples with higher concentration have higher pollutant removal. R2 , RMSE, and MAD of ANN modeling showed high correlation and precision between experimental and predicted results. Based on the results, pH adjustment is an effective method for removing heavy metals from wastewater. Also, ANN is an appropriate method for modeling and predicting of chemical precipitation
