The effective management of forest resources is very important for the future of the forest and to meet both ecological and economic needs. In this study, it is aimed to contribute to the applicability of modeling in practice by identifying regions that may be landslide in forest areas via different modeling approaches. A total of six models were created by using four criteria (elevation, slope, aspect and stream power index) and using Fuzzy Inference System (FIS) and Modified-Analytic Hierarchy Process (M-AHP) approaches in this study. The model's performance was measured using the Receiver Operating Characteristic (ROC) curve and Area Under Curve (AUC). According to the results of study, the most successful model was determined as FIS Model 1 with the AUC value of 82.1% and M-AHP Model 1 with the AUC value of 80.9%. This study provides important outputs that indicates the potential benefits of using landslide susceptibility mapping in the fields of forest harvesting, road network planning and forest management.