Mental health has become a growing concern in today’s fast-paced and stressful world, where individuals often struggle to track and manage their emotional well-being. To address this challenge, this project presents an AI-Based Mental Health Tracking and Support System that helps users monitor, reflect, and improve their mental wellness through intelligent mood analysis and self-care tracking. The system enables users to record daily moods, journal entries, affirmations, goals, and gratitude reflections, creating a comprehensive emotional profile over time. Developed using Python and Streamlit, it provides an interactive dashboard where users can visualize emotional trends, view history, and track progress through engaging data charts. All user inputs are securely stored in a SQLite database, ensuring persistence and easy retrieval. The system promotes self-awareness, consistency, and emotional balance by offering structured journaling and progress insights. By integrating automation, visualization, and data-driven reflection, this project aims to support mental wellness in an accessible, private, and user-friendly way.