Conventional deforestation risks models rely on linear approaches, failing to account for causal relationships among drivers. Yet several factors such as energy demand, urbanisation and agricultural expansion play different roles in deforestation. We propose a novel method integrating GIS-based spatial analysis and structural equation modeling to quantify direct and indirect effects of deforestation drivers. Results show that energy demand is a primary driver of deforestation and urbanization, while urbanization itself does not directly cause deforestation but influences indirectly through increased energy demand. This scalable model offers insights to support decision-making for balancing climate, urbanisation, energy security, and forest conservation.