The Sundarbans Mangrove Ecosystem (ME), the world’s largest contiguous mangrove forest, is undergoing significant changes due to increasing human activities and climate-related stressors. This study provides a detailed spatiotemporal analysis of land cover changes across the Indian Sundarbans using MODIS decadal land cover data (2000–2020) combined with Markov Chain modeling to forecast future scenarios up to 2050. The methodological framework incorporates remote sensing classification, spatial statistics, transition matrix analysis, and predictive simulation within a Geographic Information System (GIS) environment. Results show a notable decline in dense mangrove areas and a growth in sparse vegetation and non-vegetative land cover types, highlighting ongoing degradation. Transition probability analysis suggests continued deforestation trends under a business-as-usual approach. Future land cover maps for 2030, 2040, and 2050 project a considerable decline in ecological resilience, with high-risk zones identified for biodiversity loss and coastal vulnerability. The findings stress the urgent need for proactive conservation efforts, adaptive coastal zone management, and strengthened community-based strategies. This integrated approach demonstrates the effectiveness of medium-resolution satellite data and Markov modeling for long-term mangrove monitoring and decision-making, especially in data-limited, ecologically sensitive areas like the Sundarbans.