The Intelligent Crop Management System (ICMS) utilizes Machine Learning (ML) and Deep Learning (DL) to offer personalized recommendations for crop cultivation, focusing on crop selection, fertilizer usage, and disease identification. By analyzing factors like soil quality, climate conditions, and historical agricultural data, ML algorithms generate tailored crop recommendations for specific locations, enhancing yield and resource optimization. DL models advise on optimal fertilizers based on nutrient requirements and soil composition, while also detecting and preventing crop diseases through early identification and actionable recommendations, ultimately contributing to sustainable agriculture practices.