Children’s emotions can affect the learning process, especially positive emotions, making them more focused on learning. In addition, in terms of identifying someone’s emotions, we can represent them through facial expressions by combining the local binary pattern (LBP) and the local ternary patterns (LTP) method, known as Co-ChiLeRFE. The reasons for combining the two methods are that the LBP has proven to be very good at performing feature extraction, especially in describing textures. At the same time, LTP is adept at dealing with uniform motifs such as those on the face area. Subsequently, in this study, we used the NIMH child emotional faces picture set (NIMH-ChEFS), which has five-class expressions: sad, neutral, happy, angry, and afraid. To achieve optimal results in the Co-ChiLeRFE method, we set the LBP parameter as P = 8, R = 8, and the LTP parameter threshold value of one. The results we got from this experiment achieved a system performance superior accuracy of 92.51%.