The increasing frequency and intensity of forest fires, driven by climate change and human activities, pose a significant threat to vital forest ecosystems, particularly where fire is not a natural element in the regeneration cycle. This study aims to identify the indicators influencing forest fire vulnerability and compare maps of forest fire susceptibility that are based on the Intergovernmental Panel on Climate Change tripartite model, with a focus on the vulnerable Hyrcanian forest region in Golestan Province, northern Iran, where forest fires have caused considerable economic losses. On the basis of expert opinions and a literature review, we used geographic information systems, remote sensing and machine learning techniques to select and weigh 30 biophysical, environmental and socioeconomic indicators that affect forest fire vulnerability in the study area. These indicators were rigorously normalized, weighted and amalgamated into a comprehensive forest fire vulnerability index to analyze forest exposure, sensitivity and adaptive capacity. We thus identified and mapped areas with very high forest fire exposure, high sensitivity and low adaptive capacity for urgent targeted intervention and strategic planning to mitigate the impacts of forest fires. The results also revealed a set of critical indicators that contribute more significantly to forest fire vulnerability (e.g., precipitation, elevation and factors related to biodiversity, human activity and economic reliance on forest resources). Our results provide insights that can inform policy-making, community engagement and environmental management strategies to mitigate the vulnerabilities associated with forest fires in the Hyrcanian forest

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