Lilium brownii (Baihe) contains several bioactive compounds with anti cancer properties. This study aimed to predict the anticancer targets and related pathways of Baihe for the treatment of gastric cancer (GC) by using network pharmacology and to further explore its potential mechanism in GC. The active compounds and their target proteins were screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The OMIM, CTD, and GeneCards databases provided information on GC related targets. After the overlap, the targets of Baihe against GC were collected. The STRING network platform and Cytoscape software were used for protein protein interaction (PPI) network and core target investigations. Network pharmacology predicted that the principal targets were retrieved from the Starbase database in connection with the GC overall survival. Molecular docking was also used to validate Baihe and the targets high affinity. Finally, the DAVID online tool was used for the overlapping target Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The TCMSP database showed that Baihe has seven bioactive components. Apoptosis and p53 signaling pathways were primarily enriched in overlapping genes according to KEGG analysis. Androgen receptor (AR) was identified as a major target by combining the PPI network, KEEG enrichment, and target gene prognostic analysis. Molecular docking results verified that the Baihe's 3 demethylcolchicine has a high affinity for the GC target AR. Based on the results of network pharmacology analysis based on data mining and molecular docking methods, the multi-target drug Baihe may be a promising therapeutic candidate for GC, but further in vivo/ex vivo research is required.