One of the most popular household animals is the dog. Numerous problems, including population management, a reduction in rabies outbreaks, vaccination control, and legal ownership, arise from the enormous number of dogs. There are more than 180 dog breeds available today. Every dog breed has unique traitsand medical circumstances. It is crucial to identify people and their breeds in order to administer the proper care and training. Machine learning provides the strength to train models of algorithms that will manage the challenges of classifying information and making predictions based solely on newly appearing information as raw data. Convolutional Neural Networks (CNNs) provide a single, widely used approach for detecting and classifying images. In this effort, we describe a CNN based method for identifying dogs in potentially complicated photos and as a result, we take into consideration the identity of a certain dog breed. Given that the conventional metrics were verified by the analysis of the experimental results, the graphical depiction verifies that the CNN algorithm provides excellent analysis accuracy across all tested datasets.