This work explores the creation of a hybrid intelligent system for classifying kidney images, merging convolutional neural networks (CNN) with fuzzy logic. The system’s goal is to extract important image features using CNNs while dealing with uncertainties and imprecision via fuzzy logic. To accomplish this, a series of steps were carried out, starting from data acquisition and preparation to ensure uniform quality. Next, CNN models were used for feature extraction, followed by implementing a fuzzy logic system for classification. The model's performance was then evaluated to determine its accuracy and sensitivity across different renal conditions.