Idiopathic pulmonary fibrosis (IPF) carries a high mortality rate and has a poor prognosis. The pathogenesis of pulmonary fibrosis (PF) is highly related to dysregulation of multiple RNAs. This study aims to identify and validate dysregulated RNAs that exhibited dynamic alterations in response to bleomycin (BLM)-induced PF. The results will provide therapeutic targets for patients suffering from IPF. Whole transcriptomic profiles of BLM-induced PF were obtained through high-throughput RNA sequencing. miRNA profiling was downloaded from GSE45789 database in the Gene Expression Omnibus (GEO). We identified the differentially expressed RNAs (DERNAs) that exhibited dynamic alterations in response to BLM-induced PF. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis were conducted to discovery regulatory processes of PF. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) analysis, and co-expression analysis were performed to identify key genes and pathogenic pattern during the progression of PF. MiRanda, miRcode, and TargetScan were utilized to predict target relationships in the potential competing endogenous RNA (ceRNA) network. The results were verified by qRT-PCR analysis. In the context of BLM-induced PF, this study identified a total of 167 differentially expressed messenger RNAs (DEmRNAs), 115 differentially expressed long non-coding RNAs (DElncRNAs), 45 differentially expressed circular RNAs (DEcircRNAs), and 87 differentially expressed microRNAs (DEmiRNAs). These RNA molecules showed dynamic alterations in response to BLM-induced PF. These DEmRNAs exhibited a predominant association with the biological processes pertaining to the organization of extracellular matrix. A regulatory network was built in PF, encompassing 31 DEmRNAs, 18 DE lncRNAs, 13 DEcircRNAs, and 13 DEmiRNAs. Several DERNA molecules were subjected to validate using additional BLM-induced PF model. The outcomes of this validation process shown a strong correlation with the results obtained from RNA sequencing analysis. The GSE213001 dataset was utilized to validate the expression levels and diagnostic efficacy of four specific hub mRNAs (CCDC80, CLU, COL5A1, and COL6A3) in individuals diagnosed with PF. In this study, we identified and validated several RNA molecules that exhibited dynamic alternations in response to BLM-induced PF. These dysregulated RNAs participated in the pathogenesis of PF and can be used as therapeutic targets for early-stage IPF. Although more work must be done to confirm the results, our study may provide directions for future studies.