Food allergies present a significant public health challenge, affecting a considerable portion of the global population with potential for severe reactions. The Detecting Food Allergies Based on Deep Learning (DEFA-DL) model represents an innovative approach, combining Convolutional Neural Networks (CNNs) and You Only Look Once (YOLO) methodologies, to accurately identify allergenic substances in various food products