Music recommender systems have become an important application of personalised technology aimed at tailoring content to users’ preferences. However, most past systems have relied almost exclusively on the users’ past interactions and similarity in content, rather than adjusting recommendations in real time based on inputs from the users’ end. This project introduces a facial recommendation system that uses a Convolutional Neural Network (CNN) to recognise the facial emotion of the user, thus creating a more immersive and contextually relevant experience. Following this, the system employs clustering and content-based recommendation methods to predict and recommend songs to the users based on their mood.