Image recognition is important side of image processing for machine learning without involving any human support at any step. In this paper we study how image classification is completed using imagery backend. Couple of thousands of images of every, cats and dogs are taken then distributed them into category of test dataset and training dataset for our learning model. The results are obtained using custom neural network with the architecture of Convolution Neural Networks and Keras API.