This study looks at the link between people’s mental health and their music preferences on the Spotify platform. Using Python and the SpotiPy library, we retrieve user data and song information from the Spotify Web API. Advanced machine learning methods, such as Naive Bayes and linear regression, are used to identify trends and predict mental health using musical qualities. Our research seeks to improve knowledge of how digital platforms such as Spotify influence emotional well-being and the varied ways music affects mental states. By investigating the relationship between musical elements and mental health indicators, we want to give insights that might be used to design digital tools and interventions for enhancing emotional health. This work makes a substantial contribution to the fields of psychology, digital platform design, and the study of technology’s role in molding human emotions and behaviors, providing useful insights into the junction of technology and human well-being.