Landslides cause enormous economic damage and fatalities worldwide. The “Mega disaster” in the mountainous region of Rio de Janeiro took place on 11 and 12 January 2011 and reached seven municipalities. This landslides event is considered the worst disaster in Brazilian history. Landslide susceptibility zonation is one of the most important tasks in landslide risk assessment. The different approaches for landslide susceptibility modelling includes: 1) Heuristics (e.g., index-based approach and an analytical hierarchical process approach); 2) Statistical (statistical index, certainty factor, probability based methods, weight of evidence modelling, multiple linear regression and logistic regression analysis); 3) Process-based or deterministic modelling (slope stability factor). In this study, the process-based model SINMAP (Stability Index Mapping) was applied to determine landslide susceptibility in Nova Friburgo municipality (Rio de Janeiro State). The most common landslide processes in the study area are shallow triggered by rainfall. Entire database was incorporated in a GIS environment to compute the susceptibility index in a single-calibration mode. Results show that 13,94 % of area includes terrains with low susceptibility; 12,1 % includes moderate susceptibility and 73,96 % a high susceptibility. Validation showed that 89% of shallow landslides mapped occurred within the three highest susceptibility classes. Final susceptibility map can be used as a predictive model for future location of mass movements. The deterministic method proved to be a reliable technique for landslide susceptibility analysis. However it is necessary to test the sensitivity to different input data sets and geotechnical parameter values to have a holistic approach.