Dogs are among the foremost common livestock. Due to an outsized number of dogs, there are several issues like social control, decreasing outbreaks like Rabies, vaccination control, and legal ownership. At present, there are over 180 dog breeds. Each dog breed has specific characteristics and health conditions. In order to supply appropriate treatments and training, it is essential to spot individuals and their breeds. This paper presents the classification methods for dogs. It relies on a project that builds a CNN (Convolutional Neural Network) to classify totally different dog breeds. If the image of a dog is found, this algorithm would notice the estimate of the breed. The given system employs innovative strategies in deep learning, also convolutional neural networks and transfer learning. The projected network is prepared to achieve associate accuracy of 93.53% and 90.86%, for two totally different datasets. The result shows that our retrained CNN model performs better in classifying dog breeds.