Objective: To predict the potential target of quercetin (Que) in the treatment of breast cancer (BC) through network pharmacological prediction. Methods: The target of Que was predicted through the SwissTargetPrediction database; BC targets were obtained through TTD database. The common targets intersection of Que and BC was obtained by mapping the target of Que and BC. The protein-protein interaction (PPI) network was constructed and analyzed through STRING database; DAVID database was used for Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Molecular docking and analysis of some common targets of quercetin-BC analyzed above. Results: 77 targets and 118 targets were selected from Que and BC, and 20 common targets were obtained from the intersection. After the protein-protein interaction (PPI) network was constructed, the post-topological PPI network composed of 13 common targets was obtained through topology. Through GO enrichment analysis, 67 biological processes, 10 cell components and 27 molecular functions were obtained. KEGG pathway analysis obtained 20 pathways. Through PPI, GO and KEGG analysis, five potential targets (KDR, AKT1, IGF1R, INSR, EGFR) of BC and Que were obtained. Molecular docking verification was performed on some of the targets, and it was found that the docking energy was low, which was consistent with the results of PPI, GO and KEGG analysis. Conclusion: The potential target of Que in the treatment of BC has been found by using network pharmacology, which provides a new theoretical idea for the follow-up treatment of BC with quercetin.