The timely and precise categorization of medical images plays a vital role in the diagnosis and management of life-threatening ailments like COVID-19, cancer, and other such diseases. This study proposes a Convolutional Neural Network (CNN)-based framework that automatically classifies diseases from medical images like X-rays, MRIs, and CT scans. CNNs, which are great at classifying images, are used in the suggested solution to automatically find and label patterns in medical images to show diseases the patient may be inflicted with. The model demonstrates exceptional performance during its training, testing, and validation phases. The study demonstrates the potential that CNN shows in helping make diagnoses more accurate and medical practice run smoother as well as the model’s potential for real-world deployment, offering reliable assistance to healthcare professionals for early disease detection.