Abstarct: The objective of this thesis is to provide a map for identifying suitable potential areas within promising zones that contain manganese reserves. In this research, geological, structural, remote sensing, and geochemical information laxyers were selected for integration within a GIS environment. The first step in preparing the map of promising areas involved identifying the necessary data. Important controls on manganese deposits in this region include the presence of faults, fractures, and specific geological features. Accordingly, fractures were delineated from satellite images, while rock units and faults were extracted using data from the ASTER and Landsat 7 sensors. This process was carried out utilizing Principal Component Analysis (PCA) techniques and band ratioing.Furthermore, appropriate filters were applied to differentiate lineaments. Ultimately, the data laxyers were integrated using fuzzy logic, resulting in a prospectivity map for manganese-bearing zones. To assess the suitability of each map, known manganese mineral locations were utilized, enabling the identification of optimal areas for continued exploration activities, which were then represented on the map. The results obtained indicate that among the applied methods, those baxsed on multi-class mapping provided a better evaluation of the region. As the prospectivity map created through the multi-class approach exhibited a higher level of correspondence with existing mineral indicators in the area, field visits were conducted to verify the identified areas against real geological conditions. Consequently, baxsed on the generated potential maps, specific locations were identified and recommended for further exploration efforts. By: Mohammad Paknezhad