This research paper aims to overcome the limits many people face when choosing outfits based on their factors, changing physical images, and the level of confidence by proposing an AI-based outfit recommendation system. This result demonstrates the system ability to deliver highly relevant outfit suggestions while minimizing misclassification errors. Users upload their pictures on the website which permits an analysis of certain features such as the skin tone, gender, and body shape of the users using some high-end image processing and machine learning techniques. The study employs a dataset of 2100 images, covering diverse ethnic backgrounds, multiple body shape (Apple, hourglass, rectangles, inverted triangle), and various clothing categories (casual, formal, traditional, sportswear). The efficiency of such a recommendation engine is tested on end-user rating and on the system’s statistical parameters demonstrating its capacity to suggest fashions that go well with the user appropriately. Our evaluation is based on multiple performance metrics: Accuracy (98.5%), F1-score (0.92), recall (0.91), and precision (0.93). This study points out the benefit of AI-based application in the fashion industry, which in particular provide a new way to design users’ shopping interfaces addressing their specific needs in detail.