Abstract-A defining part of 2020 is the COVID-19 and how it has rapidly spread across the whole world. Due to its infectious nature, it is important to be able to detect its presence in someone as quickly as possible to prevent spreading it further. Here we leveraged pretrained models such as AlexNet [9], VGG-19 and ResNet-50 [6] to speed up the training process and train our own convolutional neural networks (CNN) on Chest X-Ray images of patients with COVID-19, pneumonia and no disease. We explore the effectiveness of using deep learning to classify patients as whether or not they have coronavirus as a faster aid to help professionals detect the virus in patients. The overall results showed AlexNet to have the highest accuracy at 88%, followed by our convolutional network in second, and then VGG-19, then lastly ResNet. The results of this study are a step forward into exploring alternative methods for classifying this prominent virus.