One of the important aspects of human-computer interaction is the detection of emotions using facial expressions. Emotion recognition has problems such as facial expressions, variations of posture, non-uniform illuminations, and so on. Deep learning techniques becomes important to solve these classification problems. In this chapter, VGG19, Inception V3, and Resnet50 pre-trained networks are used for the transfer learning approach to predict human emotions. Finally, the study achieved 98.32% of accuracy for emotion recognition and classification using the CK+ dataset.