Abstract: OBJECTIVE to explore the molecular mechanism and material basis of treating pulmonary fibrosis with yifei jianpi prescription based on network pharmacology, molecular docking and chemical informatics. METHODS TCMSP and TCMID database were used to download the compounds of 11 traditional Chinese medicines. Prediction of potential targets was made by SwissTargetPrediction, Cytoscape was used to construct a chemical-target network. TTD and Drugbank screened pulmonary fibrosis related targets, constructed target protein interaction(PPI) network and conducted gene function GO analysis and KEGG pathway enrichment analysis in String database. Further, molecular docking technology was used to evaluate the affinity of key compounds with αvβ6 and Hierarchical Clustering analysis was carried out on the compounds with high activity.RESULTS There were 27 targets of yifei jianpi prescription and pulmonary fibrosis. PPI analysis yielded 6 key targets, 336 GO items and 35 KEGG pathways. Molecular docking was used to obtain 30 pharmacokinetic active compounds with potential affinity forαvβ6. ER o5 and scoring rankings were used to select 30 combinations for chemical informatics cluster analysis. Naphthol aS-bl phosphate, Tangshenoside IV_qt, (2R)-2-azaniumyl-3-(1H-indol-3-yl)propanoate, (3S)-3-azaniumyl-4-hydroxy-4-oxobutanoate and(2R)-2-Formyloxy-3-phosphonooxypropyl formate had potential inhibitory activities against pulmonary fibrosis. CONCLSION This study is expected to provide a systematic research method of bioinformatics, network pharmacology, molecular docking and chemical informatics for the treatment of pulmonary fibrosis caused by SARS-CoV-2 in traditional Chinese medicine and the related medical prescription.