This document presents a method to estimate the nitrogen content in maize leaves using image processing techniques. Images of maize leaves are taken under different lighting conditions and preprocessed to remove noise. Color and texture features like entropy, mean, variance and average energy are extracted from the images. A regression model is developed to correlate these image features with nitrogen content values obtained from chemical tests. The regression model can then be used to estimate nitrogen content from new leaf images based on their extracted features. The proposed method provides a faster estimation of nitrogen compared to traditional chemical tests and may help optimize crop yields.