Objective: To predict the target of peach kernels in the treatment of Parkinson's Disease (PD) through network pharmacology. Methods: The chemical composition of peach kernels was retrieved through the TCMSP database (https://tcmspw.com/tcmspsearch.php), and the targets of peach kernels were predicted through the SwissTargetPrediction database (http://www.swisstargetprediction.ch/). Collect PD corresponding targets through TTD database (http://db.idrblab.net/ttd/) and Drugbank database (https://www.drugbank.ca/), obtain the intersection of peach kernels and PD targets, and perform protein -Protein interaction network analysis, from which highly related targets can be obtained. GO enrichment analysis and KEGG pathway analysis were performed through the DAVID database (https://david.ncifcrf.gov/tools.jsp). Results: 23 compound components and 274 targets were screened from the traditional Chinese medicine peach kernels, and 31 common targets were obtained by intersecting with the 155 targets of PD. The protein-protein interaction network analysis of the common target has 205 nodes, 732 edges, and 28 PD-peach kernel related targets. A topological protein-protein interaction network consisting of 92 nodes and 426 edges was screened by topological indicators, of which 22 targets were highly correlated. GO annotations yielded 105 biological processes, 30 cellular components involved, and 31 molecular functions. KEGG analysis has 33 pathways. Conclusion: Network pharmacology intuitively shows the multiple components, multiple targets, and multiple pathways of peach kernels in the treatment of PD, which provides a theoretical basis for the follow-up peach kernels to treat PD.