This study presents the r.landslide tool, an open source add-on to the open source Geographic Information System (GIS) GRASS software for landslide susceptibility mapping. The tool was written in Python language and works on the top of an Artificial Neural Network (ANN) fed with environmental parameters and landslide databases, such as: DTM, NDVI, Aspect, Geology, Faults, Plan Curvature, Profile Curvature, Rivers, Roads, Slope, No Landslide Zones (NLZ). In order to illustrate the application and effectiveness of the developed tool, a case study is presented for the Van Yen district, Yen Bai province, Vietnam. The resulted map with four landslide susceptibility classes: Low, moderate, high and very high susceptibility for landslide, which are derived based on the correspondence with landslide inventory. The map indicates that about 42 % of the area is very high and highly susceptible for landslide. The landslide susceptibility map can be useful for the decision - makers and planners in choosing suitable locations for the long - term development.