Assam, one of India’s richest regions in terms of biodiversity, faces significant environmental threats due to regional climate variability and anthropogenic pressures. This study explores a GIS and machine learning (ML)-based approach to assess the impact of climate change on forest and biodiversity vulnerability across the state. This analysis involves eight parameters: the Biological Richness Index (BRI), Disturbance Index (DI), Forest Canopy Density (FCD), Fire Point Intensity (FPI), Biomass Extraction Intensity (BEI), Slope, Standardized Precipitation Index (SPI), and Flood Vulnerability Index (FVI). Using the Analytical Hierarchy Process (AHP), these indicators were weighted and synthesized to develop a composite Forest and Biodiversity Vulnerability Index (FBVI). The major focus of this study is the delineation of climate change hotspots and their correlation with forest and biodiversity vulnerability zones. The assessment identified 19 grids as very highly vulnerable and 68 grids as highly vulnerable in terms of their forests and biodiversity. Climate change hotspot mapping revealed a further 38 grids experiencing very high climate exposure and 47 grids with high climate exposure which significantly overlap with vulnerable forested regions. This correlation suggests that regions with high climate sensitivity are also at increased risk of forest degradation, biodiversity loss, and ecosystem instability. An analysis of the trend over 22 years indicates a 1.56% decline in total forest cover and a 4.06% reduction in very dense forest cover, driven by factors such as a 9.3% increase in cropland area and a 1% expansion in settlements. The FPI analysis highlights six districts as very highly prone to fire incidents, while nine districts are highly prone to such events. The Standardized Precipitation Index (SPI) trends classify seven districts as very highly drought-prone zones, further exacerbating forest vulnerability. The Flood Vulnerability Index (FVI) identifies regions highly susceptible to flooding, stressing the compounded impacts of hydrological changes on Assam’s forest ecosystems. The results emphasize the urgent need for climate-adaptive forest management strategies, including remote sensing-based monitoring, participatory conservation approaches, and policy-driven interventions.