Sentiment analysis represents a contemporary approach in Natural Language Processing used to determine the sentiment of a user. Bangla music, with its unique rhythms, melodies, and lyrical depth, stands as a musical treasure that reflects the soul of the Bengali culture. This music serves as a powerful storyteller, narrating tales of love, sad, longing, joy, and resilience. From the soulful tunes of Rabindra Sangeet to the electrifying beats of contemporary Bangla pop, this music genre captures the essence of Bengali life and spirit. It transcends borders, touching the hearts of listeners worldwide with its timeless beauty and profound lyrics, making it a cherished part of global music heritage. This research endeavors to explore Bangla music comments reviews through the application of various machine learning classification algorithms on a dataset comprising over 2224 raw entries. Data was collected from individuals of all age groups. Following data pre- processing and feature engineering, the model was trained using Random Forest (RT), Decision Tree (DT), Multinomial Naive Bayes (MNB), Xtreme Gradient Boosting (XGB), K- Nearest Neighbor (KNN), and Support Vector Machine classifiers (SVM). These classifiers