Abstract
Accurate prediction of crop yields plays a pivotal role in modern agriculture, enabling informed decision-making for resource allocation and food security planning. This study presents "Harvest Horizon," a comprehensive crop and yield prediction model designed to enhance agricultural sustainability. The model leverages a combination of historical crop data, satellite imagery, weather patterns, and machine learning algorithms to forecast crop yields with high precision. By harnessing the power of data-driven approaches, Harvest Horizon offers a proactive solution to address the challenges posed by fluctuating climatic conditions and evolving agricultural practices. This research contributes to the advancement of precision agriculture and offers a promising tool for optimizing resource utilization, mitigating risks, and fostering global food security.