The detection of brain cancer presents a critical healthcare challenge, necessitating precise and efficient diagnostic systems. This paper introduces a comprehensive approach utilizing Convolutional Neural Networks (CNNs) and deep learning techniques for early detection. Leveraging advanced image processing, a meticulously curated dataset, and a Flask API for integration, the system offers real-time processing capabilities. The front-end interface, designed for usability and accessibility, complements the robust backend infrastructure. Through meticulous algorithmic design and optimization, the system demonstrates sensitivity and specificity in identifying brain tumors. This project represents a significant advancement in medical diagnostics, poised to enhance healthcare accessibility and contribute to scientific exploration in brain tumor diagnostics.