Abstarct: Separation of geochemical anomalies from background is a crucial task in geochemical explorations and requires a conscious chosen of an appropriate method for decomposition of geochemical anomaly patterns. The probability plot, concentration-area (C-A) fractal method and U-spatial statistics model are reliable methods for identifying the anomaly populations. In this study, by using of the stream sediment geochemical data of Feizabad, 28 elements were selected for statistical and geochemical investigations. baxsed on this studies, finally, 10 elements including Au, Ag, As, Au, Cr, Cu, Hg, Ni, Pb, Sb and Zn were selected for recognition of geochemical patterns in the study area. Principle component analysis (PCA) was applied onto the selected elements which are related to mineralization in order to derive multi-element geochemical signature. The various methods of anomaly-background separation such as probability plot, C-A fractal model and U-spatial statistics method have been applied for delineating the geochemical patterns and then promising areas. The obtained anomalous populations of U spatial statistics model in comparison with rest of models demonstrate more positive spatial association with the locations of Cu and Au-Cu occurrences within the study area. For mineral potential modeling (MPM), 7 evidential laxyers as main criteria including geochemical, geological-structural and remote sensing laxyers were selected. The scores of second component (PC2) were selected for generating the geochemical laxyer. The geological-structural laxyers consisting of proximity to mineralization-related units and intrusive contacts and fault density. Proximity to hydrothermal alterations of Phyllic, argillic, propylitic and iron-oxide are other applicable laxyers. In this study, MSLarge function was firstly used to transfer the stretched-values of evidential laxyers into (0-1) domain and then AHP as a knowledge-driven method were employed to generate final MPM model. The quantitative evaluation of AHP results displays a good agreement (84 percent) by Cu and Au-Cu occurrences within the study area and the new prospective areas have been introduced.