Utilizing facial recognition technology, the current study has attempted to predict the likelihood of student conceptual change with decision tree models based on the facial micro-expression states (FMES) students exhibited when they experience conceptual conflict. While conceptual change through conceptual conflicts in science education is a well-studied field, there is little research done on conceptual change through conceptual conflict in terms of students' facial expressions. As facial expressions are one of the most direct and immediate responses one can get during instruction and that facial expressions are often representations student's emotions, a link between students' FMES and learning was explored. Facial data was collected from 90 tenth graders. Only data from the 72 students who made incorrect predictions were analyzed in this study. The concept taught was the relationship between boiling point and air pressure. Through facial recognition software analysis and decision tree models, the current study found Surprised, Sad and Disgusted to be key FMES that could be used to predict student conceptual change in a conceptual conflict-based scenario.