The main driver of the Indian economy is agriculture. Its contribution to the GDP sector is 17.9%, based on current statistics. Plant growth is significantly influenced by nutrients. Plant development and crop productivity are negatively impacted by nutritional deficiencies. Using machine learning and deep learning, this little research investigates a novel approach to identifying nutritional deficits in plants. The method uses convolutional neural networks (CNNs) to examine plant leaf photos and detect indications of several nutrient deficits, including those related to potassium, phosphate, and nitrogen, in addition to healthy samples. The proposed model's remarkable accuracy in identifying the plants' nutritional statuses suggests that it could be useful for real-time agricultural monitoring.