Abstarct: Combining exploratory data have great importance in the determination of promising areas for mineralization and mineral potentials. Bayesian and Dempster-Scheffer methods are useful tools for integrating of exploration data. The purpose of this study is determination the promising mextallic mineralization areas using a combination of exploration data in the 1:100,000 Gonabad sheet. In this study, after reviewing and processing of remote sensing, geological, structural and geochemical data of the study area, exploration map of probability of anomaly in Bayesian method, belief map of anomaly and also uncertainty about existence of reserve were extracted in this area. In order to characterize geochemical anomalies, dendrogram and factor analysis methods were used in SPSS software. Also, probability diagrams of MATLAB software were used for separating context and anomaly. Satellite images processing is done in the ENVI software environment to detect alterations in the area. The important lithological units related to copper, lead and zinc mineralizations as well as faults were plotted from geological map of the area. The dispersion maps of copper, lead and zinc mines were prepared for validation and initial probability values. The information laxyers obtained under the programs written in MATLAB software were combined by Bayesian and Dempster-Scheffer methods. The results were compared with the dispersion map of mines and the error rates were calculated for each method. At the end, 10 important points of each method were selected and proposed for drilling and mining operations.