A connoisseur is capable of identifying the genre and artist of an art piece by inspecting various properties of the art. However, human judgment is often subjected to errors, and visually inspecting all the small details in a fine art is a tedious process and takes a long time. A question then arises: can a neural network model perform better in this task? The dataset for this project consists of 6669 images of fine art paintings by 38 influential artists. This project aims to classify the images into 20 different genres by differentiating the colors and geometric patterns in the images. Different Convolutional Neural Networks will be used as our model.