To prevent the extinction of species, continuous monitoring of wildlife is essential. As a part of monitoring, Biologists and Ecologists are using camera traps. Camera Traps use motion sensitive cameras to collect large number of images of species. Due to camera traps, image collection of animals sped up but manually analyzing and processing the images is taking more time. Hence automating the classification of images is essential to fasten the processing and analysis of images. This paperwork scrutinizes the performance of deep learning models such as ResNet50, VGG16, VGG19, Xception for classification of animal species in the images. Hence in this, the overall comparison of accuracy of deep learning models has been discussed.