Abstarct: In mineral potential modeling in order to identify exploration targets and to prepare mineral potential map, several exploratory data are used to produce the weighted control laxyers. In fact, the mineral potential modeling is a multistep process involving the production of control maps, composition of them and the ranking of the mining promising areas. So, in the all of mineral potential modeling methods; after definition of the conceptual model for a deposit and selection of suitable exploration criteria, the weighted control laxyers are produced and combined together. In this thesis, to prepare a promising area map of porphyry copper in Tarom sheet (1:100000) we applied a knowledge-baxsed inference networks using continuous fuzzification. In the Tarom sheet, there are several important mineralization factors such as mine indeices, acidic to intermediate intrusive rocks, volcanic rocks, alteration phenomena and tectonic setting; cause to this area well be mineralization zone and has to some promising area. In this research for preparing information laxyers, geologic, remote sensing and geophysical data have been used. Using satellite images (ETM+ and ASTER data) and different techniques for image detection, such as principal component analysis and band ratio methods and edge detection filters, surface spread of the alteration phenomenon, rock units and structures and lineaments were identified. As well as to identify lineaments and faults in this area geological maps, aeromagnetic and satellite imagery were used. In addition to derive the best combination of multi-element mineralization reagents, analysis of stream sediment geochemical data are used. After the alteration, fault density, watershed and intrusive maps were prepared; a suitable logistics function was used for wrapping laxyers in to the range of 0 to 1. The weighted continuous control laxyers are combined using fuzzy operators. In this study, to improve the outcome of the exploration of mineral resources and determine promising areas for detailed exploration, Mineralization modeling has been done baxse continuous weighting on geological factors. In addition, in order to avoid arbitrary weighting and classification continues fuzzification method was used in the process. According to remote sensing studies and taking into account the factors such as alteration, igneous lithologies, linear and ring structures, and geochemical indicators were identified promising areas.