Due to running out of fossil fuel energy resources, emerging natural and environmental hazards and increasing energy costs in most industrialized countries, deploying clean and renewable energy is rapidly developing in recent years. Among those renewable energies, the geothermal energy is considered as one of the most important one. The consumption of geothermal energy is highly dependent on the depth, volume, and power level of the source. Based on these parameters, the procedure of the direct geothermal energy usage for heating purposes and electric energy generation in power plants would be different. Geothermal energy resources are spatially distributed in many parts of the world. However, in cases where suitable geological and tectonic settings are present, the existing geothermal energy could be exploited technically and economically. The conditions for a geothermal resource to occur, is determined through exploratory works in regional and local scales. In previous studies, the potential of geothermal resources in Iran has been proven to have close association with recent volcanic extrusives. The next exploration phase is to study these promising areas to determine physical and geometrical characteristics of corresponding geothermal resources in more details. In this study, areas with high geothermal potential at Bostanbaad 1:100000 geological map are mapped using GIS environment and tools. Exploratory data layers used in current study are derived out of geological, remote sensing and geophysical studies, which were then inputted into some commonly, used layer integration methods. For this purpose, the input layers known to have meaningful association with geothermal resources are identified in the first step. These layers are categorized as geological (lithology and fault), geophysical (airborne magnetic and gravimetric data) and remotely sensed outputs (alteration of land surface temperature) were then derived and processed accordingly. In order to find favorable geothermal signatures pointing to young volcanic outcrops, shallow intrusive rocks, tectonically favorable and hydrothermally active areas, the input layers were integrated. The data integration phase were done through applying Boolean, Fuzzy logic and Dempster-Shafer methods on same input layers and the results were evaluated and compared. The results showed that although all of these three integration models could map areas with highly favorable geothermal resources to be proposed for next step follow up exploration, however the dempster-shafer model gave more information and refined output maps. These areas contain very small percentage of Bostanabad sheet, which results in lowering next step exploratory costs in addition to more specific and refined targets