Fashion and fashion trends are continually shifting, driven by increasing consumer desire to keep up with the current fashions. To meet this need, personalized clothing recommendations have grown in popularity. Moreover, the social media interaction has decentralized style, allowing fans to share inspiration and creativity. In such a dynamic environment, AI-powered fashion and outfit recommendations blossom. This paper aims to contribute to the expanding landscape of fashion recommendations by offering a sophisticated model that smoothly integrates user prompts with cutting-edge AI capabilities. The model, which is intended to deliver the top 5 outfits based on user inputs, uses natural language processing (NLP) for text embedding’s and TF-IDF as its foundational model. In addition, we use a popular clustering technique, K-means, to improve the recommendations provided by our suggested fashion recommendation system.