Coral bleaching, often triggered by oceanic warming, has a devastating impact on coral reef systems, resulting in substantial alterations to biodiversity and ecosystem services. For conservation management, an effective technique is needed to not only detect and monitor coral bleaching events but also to predict their severity levels. By combining high-resolution satellite measurements (Sentinel-2 Multispectral Instrument) and a bottom reflectance model within a least-squares approach, we developed a new ocean color remote-sensing model specifically designed to detect, map, and predict severity levels (low to high) of coral bleaching events at a high spatial resolution of 10 m. The proposed algorithm was implemented and tested within the Red Sea and compared remarkably well with concurrent and independent in situ data. We also applied the algorithm to investigate the response of corals during and after a bleaching event in the Wadi El-Gemal region (Egypt) from July to December 2020. Our results show that coral bleaching severity levels and sea surface temperature (SST) were unusually high during August–September 2020. After the event, the coral bleaching signal decreased concurrently with SST during October–November 2020, aligned with a recovery of bleached coral reefs by December 2020. The proposed algorithm offers a cost-effective approach toward developing a near-real-time remote-sensing system for monitoring coral bleaching events and recovery at multi-reef scales. Such remote-sensing tools would aid policymakers and managers in developing and implementing integrated management strategies for coral reef conservation, as well as in supporting reactive management plans, including the identification of priority areas for intervention.