The kidney is an essential organ that filters and excretes waste products to maintain the body’s fluid and solute balance. Several hormones are also secreted by it, which aids in blood pressure regulation. Kidneys also purify the blood by removing waste and impurities from it. Tumors (cancers) are brought on by uncontrolled cell proliferation, which affects people differently and results in several symptoms. Kidney cancer is indeed a significant health concern worldwide. Kidney cancer cases now days have risen in everywhere caused by a variety of elements, such as changes in lifestyle, enlarged screening and detection, and aging populations. The illness known as kidney disease has initiated on either renal disease. It is the part of essential disorders for patient diagnosis and classification in the current investigation. Timely screening along with effective action can stop or slow the succession of cancer in anticipation of too late to save the patient's life and dialysis or a kidney transplant are the only options left. This study suggested using deep learning models like convolutional neural networks to recognize kidney pictures with Computed Tomography which is also known as CT images. This study uses CNN with additional convolution layers to distinguish between images of healthy and cancerous kidneys. With the use of X-rays, CT imaging produces cross-sectional images that offer exceptional detail of internal structures and organs, making it an excellent diagnostic tool. Many patients’ lives will be saved by this research's early and accurate kidney cancer identification.