At present, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world, and the best way to effectively carry out drug diagnosis and treatment presents difficulties for all medical staff. In China, some traditional Chinese medicines (TCMs) have been successfully applied to the treatment of SARS-CoV-2 and have achieved good clinical results, including the Reyanning mixture. In this study, we systematically analyzed the mechanism of the Reyanning mixture and its effects against SARS-CoV-2 based on the method of network pharmacology. Here, we used the TCM Systems Pharmacology database and employed a similarity algorithm to screen and identify the bioactive ingredients and potential targets of the Reyanning mixture. The GeneCards database was used to predict and screen the disease targets and build the active ingredient target network diagram. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to construct the target signal pathway associations. The STRING tool was used to reconstruct the protein-protein interaction network. As a result, 27 candidate targets, such as tumor necrosis factor, interferon gamma, tumor protein P53, C-reactive protein, and peroxisome proliferator-activated receptor gamma, were identified among the 33 bioactive ingredients of the 4 TCMs in the Reyanning mixture with effects on treating SARS-CoV-2. These targets were significantly enriched in 20 KEGG pathways and associated with 48 diverse GO terms. All of these targets may play a role in inhibiting inflammatory reactions, regulating immune function, and reducing lung injury to achieve the purpose of treating SARS-CoV-2.