With the enormous increase in the number of vehicles that are making use of roadways day by day, traffic congestion is one of the significant issues that are being observed. This problem can be addressed with proper traffic regulation. In this paper, proposing an automated system that will perform traffic analysis from the traffic videos which were captured from static cameras. This traffic analysis will be performed in three stages: vehicle detection, vehicle classification, into ten major categories, followed by vehicle counting under each category. The proposed work adopting the background subtraction method and vehicle classification by using a pre-trained model VGG16 as well as logistic regression (LR). Observations were made across several models ranging from the models that were built from scratch to pre-trained models as well as VGG16 + logistic regression. Experimental results show that the proposed model provides top-1 accuracy of 84.32% and top-5 accuracy of 99.77%.