Objective To investigate the role of necroptosis key genes in spinal cord injury using bioinformatics methods to provide new targets for the diagnosis and treatment of spinal cord injury. Methods The peripheral blood transcriptome data of spinal cord injury samples (n=38) and healthy control samples (n=10) were obtained from GSE151371 data set in Gene Expression Omnibus (GEO) database. R software was used to identify differentially expressed genes and perform functional enrichment analysis. Machine learning algorithms (random forest and LASSO) and protein-protein interaction (PPI) networks are used to screen for necroptosis key genes and construct a diagnostic nomogram for spinal cord injury. Establish a rat spinal cord injury model to further verify the expression of necroptosis key genes by Western blotting and immunofluorescence staining. Results A total of 2050 differentially expressed genes were identified in the two groups. KEGG pathway enrichment analysis showed that the differentially expressed genes were involved in the nucleotide-binding oligomerization domain (NOD)‑like receptor signaling pathway, hematopoietic cell lineage, and necroptosis; GO enrichment analysis showed that the differentially expressed genes were involved in the activation of leukocytes, tertiary granulation, and regulation of the defense response, and so on. Intersection analysis screened 15 necroptosis differentially expressed genes. KEGG pathway enrichment analysis showed that necroptosis differentially expressed genes were involved in necroptosis, influenza, and NOD-like receptor signaling pathways; GO enrichment analysis showed that necroptosis differentially expressed genes were significantly enriched in the cellular response to cytokine stimulation, cytokine-mediated signaling pathways, and response to cytokines. Integration of two machine learning algorithms and PPI analysis further screened two necroptosis key genes (IL1B and PLA2G4A). The nomogram established using IL1B and PLA2G4A can be used for early prediction of the occurrence of spinal cord injury. The validation results of the rat spinal cord injury model showed that the protein expression of IL-1β and PLA2G4A in the spinal cord injury group were significantly higher than those in the sham group (P<0.05). Conclusions IL1B and PLA2G4A as key genes of necroptosis involved in the development of spinal cord injury, can be used to predict the development of spinal cord injury with the promise of being new targets for the prevention and treatment of spinal cord injury