With the advantages of real time analysis and visual evaluation results, intelligent technology-enabled teaching behavior evaluation has gradually become a powerful means to help teachers adjust teaching behaviors and improve teaching quality. However, at present, the evaluation of intelligent teachers’ behaviors is still in the preliminary exploration stage, and the application research is not deep enough. This paper analyzes the application of intelligent technology in the evaluation of teachers’ classroom teaching behaviors from the perspectives of evaluation data, methods, and results. Voice print recognition technology is used to recognize the teachers’ identities and track the speech in the classroom videos, and the videos are segmented. Then, the evaluation framework of teachers’ classroom teaching behaviors is constructed using three dimensions of emotion, posture, and position preference. Finally, evaluation results are presented to teachers in a more intuitive and easy to-understand visual way, to help teachers reflect on teaching. This paper aims to promote the transformation of teachers’ classroom teaching behavior evaluation toward an intelligent, efficient, and sustainable direction through current research.