Coral reefs are vital for marine biodiversity, coastal protection, and millions of livelihoods worldwide, but coral bleaching poses a significant threat to their survival. Triggered by rising sea temperatures and environmental stressors, bleaching leads to the expulsion of algae essential for coral health, causing widespread reef degradation. This has severe implications for ecosystems, fisheries, and coastal communities. To predict and analyze coral bleaching, we developed a machine learning-based regression approach and a web application for real-time monitoring and prediction. The study utilized datasets from two regions: global waters and the Indian Ocean. For the global dataset, the Extra Trees Regressor achieved the best performance with an Adjusted R-Squared of 0.68 and an RMSE of 10.47. On the Indian Ocean dataset, the Random Forest Regressor excelled with an R-Squared of 0.676 and an RMSE of 14.96. The web application aids researchers and policymakers with accurate predictions, supporting effective strategies to mitigate coral bleaching and preserve marine ecosystems for sustainable ocean management.