This project explored Deep Learning’s capability in detecting brain tumors within MRI scans. It reviewed various types of algorithms, any benefits and drawbacks, and performed a comparative analysis to identify the models’ accuracy and potential usage in a clinical environment. It took into consideration the risks of individual error types and provided recommendations for usage going forward.