In order to prevent any damages which can be caused by flood at Haraz watershed in the Mazandaran province, it is essential to prepare a flood susceptibility map using logistic regression. About 211 flood locations and 211 non-flood locations were first recognized. Ten flood conditioning factors such as Slope, plan curvature, altitude, distance from river, topographic wetness index (TWI), stream power index (SPI), rainfall, landuse and normalized differences vegetative index (NDVI) were then identified. The maps of all affecting factors were prepared using ArcGIS10.1, ENVI 5.1 and SAGA GIS2 software and they were exported to raster formats. Flood locations were randomly divided into two groups: 70% (151 flood locations) and 30% (60 flood locations) for modeling and validation, respectively. Enter method was selected for weighing the 10 factors in SPSS.18. The factors with their corresponding weights were used in the ArcGIS software for generation of flood susceptibility map. The map was divided into 5 classes. ROC curve and area under curve (AUC) are used for the validation of derived map. The results indicated that for prediction rate, the AUC is 78.3%; thus, the logistic regression has a reasonable accuracy for flood susceptibility mapping. The findings of this research are useful and necessary for scholars, the Mazandaran Regional Water Authority (MRWA), Ministry of Energy, and other agriculture and natural resources-related organizations in order for mitigating losses and damages during flooding events.