Objective: To study the effective compound action target signal pathway of Peiyuan bushenan taifang(PYBSATF) has achieved good clinical efficacy in the treatment of recurrent spontaneous abortion(RSA), but its mechanism has not been clarified because of its complex components. In this study, network pharmacology is applied to study the effective compounds, targets and signal pathways of PYBSATF in the treatment of RSA, so as to reveal its pharmacological mechanism of action in the treatment of recurrent spontaneous abortion. Methods: The Traditional Chinese Medicine Systems Pharmacology database(TCMSP) and CNKI are used to obtain the main compounds and drug action targets of PYBSATF. Genecards and the Online Mendelian Inheritance of Man databases (OMIM) are searched to collect the known genes related to RSA, so as to construct compound- target network and screen out the common target proteins and main active compounds.We also use string database to construct a visual protein-protein interaction network (PPI). Cluster Profiler and R software were used to analyze the common targets of drugs and diseases for GO function analysis and KEGG pathway enrichment analysis.Finally,the compound and the protein sequences were conducted according to the node parameters, so that the core protein and core compounds are used to perform molecular docking. Results: 186 potential active components and 65 predicted action targets of PYBSATF were screened out. At the same time,1658 genes were also screened out to be closely related to RSA, among which 65genes overlaped with PYBSATF targets and were considered to be related to way of treatment. PPI network showed that VEGFA,IL6,EGFR, MAPK8 and ESR1were the core targets of PYBSATF for the treatment of RSA. GO and KEGG enrichment analysis obtained 93 biological processes of cells (P < 0.01) and 87 signaling pathways (P < 0.01). PYBSATF played a pharmacological role through a variety of pathways including anti-inflammatory,anti-apoptosis,promoting proliferation and angiogenesis. Molecular docking showed that most active components and key targets of PYBSATF had strong efficiency. Conclusion: Through the study of network pharmacology,it predicted that PYBSATF might treat RSA through multiple targets and multiple signal pathways. Significantly, the predictive targets may be potential targets for treatment of RSA.