Leukocytes, or white blood cells, are produced in the bone marrow and constitute about one percent of all blood cells. Their uncontrolled proliferation results in various forms of blood cancer, notably Acute Lymphoblastic Leukemia (ALL) and Multiple Myeloma (MM). ALL is characterized by an overproduction of lymphocytes in the bone marrow, while MM leads to the accumulation of malignant plasma cells, which inhibit the generation of healthy blood cells. Traditional diagnostic methods rely heavily on manual classification by skilled professionals, making the process time consuming and prone to human error. To address these limitations, this study presents an automated approach utilizing deep learning techniques, specifically convolutional neural networks (CNNs), to classify ALL and MM effectively.