aspg-41-4437-1792223478 20261017075118 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Metaheuristic Optimization Review MOR 3066-280X 2026 6 1 Karim Eldreny Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt Brain tumors are serious neurological conditions that require accurate and timely classification to support medical evaluation and treatment planning. This project presents a deep learning-based system for classifying brain Magnetic Resonance Imaging (MRI) scans into four categories: glioma, meningioma, pituitary tumor, and no tumor. The proposed system uses a Convolutional Neural Network (CNN) trained on a balanced dataset of 7,200 MRI images collected from publicly available sources. The images were preprocessed through RGB conversion, resizing, tensor transformation, and normalization to ensure consistent input for model training and testing. The trained model achieved an overall classification accuracy of 94.31% on a held-out test set of 1,600 MRI images, demonstrating strong performance in multi-class brain tumor classification. A Streamlit-based web application was also developed to allow users to upload MRI images and view the predicted class, confidence score, and probability distribution across the four categories. The system is intended for educational and research purposes only and should not replace professional medical diagnosis, clinical judgment, or radiological evaluation. 2026 103 117 4437 https://creativecommons.org/licenses/by/4.0/ 10.54216/MOR.060108 https://americaspg.com/journal/41/article/4437 https://americaspg.com/storage/articles/manuscripts/01KW0KDHWDE9EBSZK9Z334A67M.pdf