Grasslands are among the world's most vital ice-free ecosystems, providing critical services such as carbon sequestration, biodiversity support, and pollination. However, these systems face increasing pressure from climate change, characterized by rising temperatures and altered precipitation patterns. Predictive models that integrate historical data with future climate scenarios are essential for anticipating shifts in biomass dynamics and developing adaptive management strategies to preserve the ecological and economic functions of grasslands. This thesis, developed in collaboration with the CEIGRAM Research Center in Madrid (central Spain), evaluates the efficacy of satellite-derived vegetation indices, specifically the Normalized Difference Vegetation Index (NDVI), as reliable proxy for pasture biomass production under climate change.