Background <p>The association between lactylation and tumor radiotherapy has become a widely studied hotspot. However, the prognostic value of lactylation-related genes (LRGs) linked to radiotherapy‑associated transcriptional changes in cervical cancer remains unclear.</p> Methods <p>Based on gene expression data from public databases and LRGs, we identified key genes for cervical cancer prognostics and verified their expression levels. Subsequently, LASSO regression with 10-fold cross-validation was used for model construction and internal validation. Patients were divided into different groups according to the optimal cut-off value of risk score, and their differences in biological function/pathway, immunoregulation, and tumor mutation burden (TMB) were analyzed. A nomogram for predicting the survival probability was also constructed.</p> Results <p>Our study identified two key genes (RFC4 and STMN1), whose expression was upregulated in tumor tissues but significantly downregulated during radiotherapy. The risk model incorporating the two genes was verified internally and exhibited favourable prognostic stratification capability. Patients were divided into high- and low-risk groups; differentially expressed genes between the groups were significantly enriched for immune-, angiogenesis-, and metabolism-related functions/pathways. Furthermore, the two groups exhibited distinct immune cell infiltration levels and gene mutation, with the low-risk group showing superior survival outcomes. Multivariate Cox analysis identified risk score, overall stage, and T stage as independent prognostic factors (<i>P</i> &lt; 0.05). The nomogram incorporating these factors effectively predicted 1-year, 2-year, and 3-year survival rates.</p> Conclusion <p>This study provides a promising prognostic model for risk stratification of cervical cancer patients and identifies two biomarkers, which will help promote the understanding of the relationship between radiotherapy, lactylation, and prognosis in cervical cancer.</p>