The increasing demand for land use and the mismanagement of lands have caused the increase of landslides around the world. It is important to recognize the landslide characteristics and the determining factors that influence this phenomenon in order to mitigate the adverse economic and environmental impacts. This study aims to estimate the landslide susceptibility in an area of Siahkal at Gilan province, Iran, by formulating a model using Gene expression programming (GEP). Seven condition factors including altitude, aspect, slope, proximity to rivers, proximity to faults, land use and lithology, were used in this research. The proposed model was developed as an equation, and its accuracy was assessed by the area under an Receiver Operating Characteristic curve that shows 0.82 and 0.77 for the training data and the test data, respectively. The result of this research was also evaluated with the inventory map over the study area which was constructed by field surveying and interpretation of airborne/satellite images. Our landslide susceptibility map indicates that the northern part of the area has the highest possibility for landslide which is in agreement with the landslide inventory map of the previous landslide

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