Modelling Land Use Land Cover Changes (LULCs) allows understanding the dynamics of the processes and their variables. Projecting future trends of LULCs facilitates the implementation and contextualization of the decision making planning. The aim of this study was to identify the most vulnerable areas to LULCs under different socioeconomic and climate change (CC) scenarios in Mexico for three time-slices 2020, 2050 and 2080. LULCs spatially explicit models were developed in the Dinamica EGO platform that uses prospective methods based on probabilistic maps. The CC scenarios were based on the Special Report on Emissions Scenarios (SRES) from the IPCC. Temperate forests, tropical dry forests and scrublands were the most affected natural covers in terms of extent while tropical evergreen forests and natural grasslands lost proportionally more extent in comparison to the other natural covers, during the periods of the inputs maps (1993-2002 and 2002-2007). According to the models, natural grasslands might be the most endangered natural cover due to LUCC and CC losing 20% and 40% of its extension in relation to 2007. Agricultural expansion has been the principal cause of natural vegetation loss, explaining from 40% to 80%, the principal explanatory variables were distance from human settlements, roads, slope, altitude, aridity, and evapotranspiration.