This project focuses on building a music genre classification system using deep learning. It utilizes MFCC (Mel Frequency Cepstral Coefficients) as audio features and combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to learn spatial and temporal features from audio data. The model is trained using K-Fold Cross-Validation, and a frontend allows users to predict the genre of an audio file.