One of the most pervasive factors in degradation of forest ecosystems is fire. Identifying the effective factors in the likelihood of forest fires occurring and spreading is one of the essential tasks in achieving fire management control and exposure. Environmental vulnerability deals with environmental hazards, sensitivity and adaptive capacity, taking into account natural conditions (natural factors and stresses) and human conditions (economic, social and human stresses). Environmental Vulnerability can help identify vulnerable areas and help make decisions to protect the environment and achieve sustainable development. In this study, mapping high risk areas of forest fires based on slope, direction, altitude, annual rainfall, relative humidity, drought frequency, maximum monthly temperature, land use and land cover, road distance, river distance, distance The density of residential centers, distance from agricultural areas, and vegetation density in the forests of Kurdistan province were 29137 km2. The fires were first obtained from the Directorate General of Natural Resources, the province's environment and field operations. The firing points were entered into R software with Shp format background points and map of factors influencing the risk of fire to run the model. The maps obtained from the models in the SDM package were combined to produce the optimal fire map using the weighted average method. The output map was divided into four categories: no risk, low risk, medium risk and high risk; of which 2% had high risk status, 12% moderate risk, 20% low risk and 66% In a safe position. Based on the results of the modeling, annual rainfall, sea level rise, slope, maximum temperature, distance from city and distance from agriculture have the most influence on the factors affecting fire risk. In order to study the sensitivity of the study area, habitat suitability of brown bear, squirrel and protected areas were used. For this purpose, areas that are favorable for both species and protected areas of the province have higher ecological value and are more sensitive. According to the results, 82% of the total area of the province had no sensitivity, 11% had low sensitivity, 5% had moderate sensitivity and 2% had high sensitivity. Finally, to assess the ecological vulnerability of the study area, the fire risk map and the sensitivity map were combined in TerrSet software. The map shows that 64 percent of the total area of the province is in the non-vulnerability category, 24 percent in the low-vulnerability class, 10 percent in the middle-vulnerability class, and 2 percent in the high-vulnerability class. Also, the cities of Saroabad, Marivan, Baneh and Kamyaran have the most vulnerable areas, respectively. Therefore, it is necessary to concentrate management actions in critical and sensitive areas and to prevent the most vulnerable areas from becoming more vulnerable. Keywords :Modeling, forest fire risk, ecosystem sensitivity, habitat suitability, Kurdistan