Agricultural drought poses significant challenges to agricultural productivity, food security, and economic stability, particularly in the face of escalating climate change. Remote sensing technology plays a pivotal role in monitoring drought conditions by providing near-real-time data on crucial indicators such as rainfall, soil moisture, evapotranspiration, and vegetation health. While traditional single-parameter indices like the Standardized Precipitation Index (SPI), Normalized Difference Vegetation Index (NDVI), etc., have been used, their limitations have prompted the development of composite indices that offer comprehensive understanding by integrating multiple data sources through advanced weighting techniques. Additionally, forecasting agricultural drought is evolving, with hybrid models showing promise in accurately predicting drought. Several global agricultural drought monitoring and early warning systems are functioning across various parts of the world such as the United States Drought Monitor, South Asia Drought Monitoring System, etc. India has also implemented its own drought monitoring and declaration system making use of science-based parameters and decision-tree-based approach. However, India still lacks a robust agricultural drought forecasting and prognosis system tailored to its specific needs for different regions. Establishing such a system is crucial for providing timely alerts and supporting proactive drought management strategies, ultimately enhancing resilience in the face of agricultural drought.