The use of traditional herbal remedies, particularly medicinal leaves, remains popular in Vietnam for treating common cold-related illnesses. However, identifying the correct leaf types and applying them appropriately poses challenges for non-expert users. This study proposes a web-based system utilizing artificial intelligence to assist in recognizing medicinal leaves commonly used in traditional treatments for colds. A dataset comprising 5,958 images of 10 different leaf types was constructed, labeled, preprocessed, and augmented to enhance model performance. A fine-tuned deep learning model based on the VGG16 convolutional neural network architecture was employed for classification and achieved an accuracy of 95.23% on the test set. The model was then integrated into a user-friendly web application that enables users to upload leaf images for recognition and receive detailed medicinal usage guidance. This system not only promotes the safe and informed use of traditional herbal medicine but also represents a meaningful step toward digitizing and preserving Vietnam’s rich ethnobotanical knowledge through artificial intelligence.