A machine learning project demonstrates how to predict blood groups using fingerprints instead of traditional blood sampling methods. The proposed non-invasive system utilizes deep learning algorithms, achieving 98% accuracy compared to the existing 85%. This innovative approach eliminates the need for chemicals and reduces time and resource consumption in blood group detection.