One of the most common surface features of Karst topography is sinkholes. The karst areas provide drinking water for 25% of the world’ s population. Identifying sinkholes is crucial in managing waterresources, as their contamination leads to the contamination of water resources in the area. The BisotunParav Karstic Basin is essential because it creates spring wells in Bisotun and Kermanshah and supplies part of their water. This study aims to detect potential areas for sinkholes using GIS and Decision MakingTrial and Evaluation Laboratory)-based analytic network process (DANP). The criteria which were usedare Climatology (precipitation, temperature, evaporation, streams), Topography (slope, elevation), Agriculture (vegetation), and Lithology (lithology, soil type, fault). Then the required layers wereobtained, and the importance of each factor was determined through a combination of the DEMATEL technique and the ANP. Finally, after combining the layers, a map of potential sinkhole areas was obtained. Sinkholes in the area were detected using the visual interpretation of world imagery and google earthimagery as reference data. The results of the DANP demonstrated vegetation, elevation, and lithology withthe value of 22. 59%, 12. 12%, and 11. 94 respectively are the most important factors involved in theformation of sinkholes. The indexes of correctness, completeness, and quality were then used to evaluate the study results and turned out to be 98. 73%, 79. 86%, and 79%, respectively. The high correctness index indicates high efficacy in detecting the existing sinkholes, but the low percentage of the other two indexes does not indicate the inefficacy of the method; rather, the two indexes of completeness and quality indicate areas with a potential for sinkhole formation that either has no sinkholes or are not in the reference data. This method effectively detects sinkholes and potential areas for sinkhole formation.