The objective of this study was to employ bioinformatics and network pharmacology methodologies to investigate the targets and molecular mechanisms of remdesivir in the treatment of coronavirus disease 2019 (COVID-19)-associated pulmonary fibrosis (PF). Several open-source databases were utilized to confirm the shared targets of remdesivir, COVID-19, and PF. Following this, a comprehensive analysis incorporating function enrichment, protein-protein interaction (PPI), transcription factor (TF), and molecular docking was conducted to investigate the potential mechanisms underlying the effectiveness of remdesivir in the treatment of COVID-19-associated PF. The initial validation of these findings was performed using publicly available histological and single-cell sequencing databases. The functional enrichment analysis revealed a strong association between remdesivir and viral defense, inflammatory response, and immune response. The key pathways identified in the study were transforming growth factor (TGF-β), PI3K-Akt, mTOR, MAPK, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance, HIF-1, and Toll-like receptor signaling pathways. Additionally, the PPI analysis demonstrated the network relationships of 13 important targets, while the TF analysis provided valuable insights into the regulatory networks of these targets. Among the identified TFs, RELA was found to be the most significant. To validate our findings, we utilized publicly available histological and single-cell sequencing databases, successfully confirming the involvement of 8 key targets, including AKT1, EGFR, RHOA, MAPK1, PIK3R1, MAPK8, MAPK14, and MTOR. Furthermore, molecular docking studies were conducted to assess the interaction between remdesivir and the identified key targets, thus confirming its effective targeting effects. Remdesivir has the potential to exert antiviral, anti-inflammatory, and immunomodulatory effects in the context of COVID-19-associated PF.