[Objective] Evidence-based research has received escalating attention in policy practice. As one of the important tools for causal inference, the global scientific community has witnessed a rapid growth of regression discontinuity design (RDD) in empirical research given its strong ability of selection bias elimination, low cost of research implementation, and less concerns of political and ethical restrictions. Yet, there are insufficient literatures that systematically reviewed RDD studies in the domain of policy evaluation, and the discussion of comparing it with other causal inference methods remains rare. [Methods] Combining both international and domestic literature indexed in Web of Science and CNKI, this paper conducts a systematic review on RDD in different policy domains. [Results]Our analysis reveals that except for the dominating fields of education, public health, environment, public administration, RDD has marked its appearance in studies of science policy as well as information science and library science. The Chinese social science community also witnessed a rapid growth of RDD research over the last decade. [Limitations] The literature scope of RDD research needs to be further expanded, and the comparative analysis with other policy evaluation methods can be further deepened. [Conclusions] The RDD research has been widely used in policy evaluation research in the fields of education, public health, environment, and science and technology innovation, etc. In the future, the method can be increased with other research methods such as quasi-natural experiments, so as to expand the application of RDD in the analysis of China's quantitative policy evaluation research and the international quantitative policy evaluation research.