Population growth, along with the development of industry and agriculture, has led to an increase in water consumption. Limited surface water resources have led to over-harvesting of groundwater aquifers and has had irreparable consequences for the country's water resources and environment, including the subsidence phenomenon, which has covered most of the country's plains. The present research aims to identify the effective factors and areas at risk of subsidence in Fadafan village of Kashmar. For risk zoning, during 2019, the lithology, land use, Petrology, aquifer Extraction rate, Distance from the stream, Fault, exploitation wells, springs and aqueducts factors as well as geomorphological factors including slope, direction and height studied and each factor turned into an information layer, then modeling and evaluation were performed using random forest algorithm in R software. Then, to determine the areas prone to subsidence, risk zoning maps in five classes were extracted using two methods of information value and area density in ArcGIS environment. The results showed that in the methods of area density and information value, 97.01 and 91.04% of subsidence were in the very- high and high-risk class, respectively. Therefore, both methods have been successful in risk zoning. Also, the aquifer extraction and land use factors are most important in subsidence. Also based on the ROC curve, random forest algorithm with very high accuracy (93%) has provided good results in prioritizing and the importance of effective factors in subsidence. The southern part of the region with rangeland use, has the highest and irrigated agriculture in the region has the lowest risk in the spatial development of land subsidence.As a result, aquifer recharge management by spreading floods and reducing water extraction in the southern part of the region can be effective and practical in reducing the risk of occurrence and development of subsidence.