In this project, I built a convolutional neural network (CNN) using TensorFlow to classify blood smear images as either parasitized or uninfected a crucial task in supporting early malaria diagnosis.I applied rigorous preprocessing, including resizing, normalization, and data augmentation to address class imbalance a common challenge in medical imaging. After training and tuning the model, it achieved strong classification accuracy, demonstrating how deep learning can assist in medical diagnostics.