Estimation of elemental distribution based on geochemical data is important for determination of elemental prospects in studied areas. The main aim of this study is to estimate Cu, Mo, Au and Ag with respect to lithogeochemical data in Kahang porphyry deposit, Central Iran, using combination of Inverse Distance Weighted (IDW) and Artificial Neural Network (ANN). The results obtained by the combination methods show that the proper elemental anomalies are associated with geological particulars including lithological units, alteration zones and faults. Moreover, correlation between raw data and the results reveals that the combination method can be applicable for interpretation of elemental distributions.