Improving how farmers manage fertilizer and predict crop yield is essential for growing food sustainably while protecting the environment. In this study, we focused on potato farming and explored how advanced technologies can help make better decisions about nitrogen fertilizer use. Traditional methods are often slow and expensive, but we used new tools, hyperspectral imaging and artificial intelligence (AI), to quickly and accurately assess plant health and predict harvest size. By collecting detailed data from the plants and using machine learning models, we were able to estimate nitrogen levels in the leaves and forecast the final potato yield. Our approach worked well across different locations, varieties, and growing conditions. These results show that AI and remote sensing can support smarter, more efficient farming practices, reduce fertilizer waste, and lower the risk of pollution, ultimately helping both farmers and the environment.