In our country, various natural hazards occur, with earthquakes, floods, and storms being among the most significant. Among these, the probability of flooding is higher, such that the damages and mortality resulting from it are constantly increasing. Therefore, the development of flood zoning and prediction models is crucial and necessary for making optimal decisions before and after a flood, as well as for its management. The objective of this research is to zone flood risk in the Lavasanat watershed using the fuzzy logic model. In this research, the most important factors affecting flooding, including precipitation data, slope, land use, and distance from waterways, were considered. These data were classified and standardized according to the intended purpose, and based on the fuzzy logic model, raster layers were weighted to prepare a flood zoning map in ArcGIS software. In this study, to eliminate the deficiencies of fuzzy multiplication and summation, a gamma operator of 0.9 was used for flood zoning. Layer weighting was based on the opinions of 30 experts in the fields of geography, natural resources, and civil engineering. A questionnaire was prepared and distributed among the experts, and they were asked to weight each factor between 0 and 1. In the final map obtained, the study area is divided into five zones in terms of flood occurrence: very high risk, high risk, moderate risk, low risk, and no risk. The results showed that the very high-risk zone covers 11.8%, the high-risk zone 11.3%, the moderate-risk zone 26.7%, the low-risk zone 30.2%, and the no-risk zone 20% of the area. In urban and rural planning, development, and construction, the requirements for flood prevention and risk reduction, including the provision of retention and storage areas, must be considered.