This system focuses on developing a comprehensive system for mental health evaluation within social media platforms utilizing Convolutional Neural Networks (CNN). The system provides an in-depth understanding of mental health, leveraging the vast amount of data generated on social media platforms for prediction and analysis through machine learning and deep learning algorithms. By monitoring the social media activities of individuals, the system aims to predict various mental health factors such as depression, anxiety, and stress. Utilizing the online social media data, the system explores the correlation between users' mental health and the content they post on their social media handles. Through this approach, mentors including teachers and doctors can access weekly analyses of individuals' stress levels, facilitating tailored consultation and support. The CNN model’s advanced capabilities offer in analyzing complex textual and visual data, enabling more accurate and nuanced evaluations of users' mental health states. Ethical considerations, including user privacy and data protection, are prioritized throughout the development and deployment of the system. By integrating this system into social media platforms, it holds significant potential to provide timely support and resources for individuals struggling with mental health issues, contributing to the well-being of users in the digital age.