Background <p>High-grade serous ovarian cancer (HGSOC) exhibits poor prognosis due to late diagnosis, chemoresistance, and limited responses to immune checkpoint inhibitors. Although tumor‐infiltrating CD8⁺ T cells correlate with improved survival, current prognostic models remain inadequate. Thus, robust biomarkers linked to CD8⁺ T cell activation are urgently needed to guide clinical management.</p> Methods <p>Transcriptomic and clinical profiles from 874 late-stage HGSOC patients were analyzed via single-sample gene set enrichment analysis for immune infiltration and weighted gene co-expression network analysis to identify CD8⁺ T cell-associated genes. An integrative machine learning approach was employed to develop a CD8⁺ T cell-associated immune prognostic signature (CIPS), which was then validated across multiple independent cohorts and benchmarked against 56 published models. CIPS was further characterized using single-cell RNA-seq analysis.</p> Results <p>The resulting 10-gene signature independently predicted overall survival in all cohorts and consistently surpassed most clinicopathological variables and comparator models. Low-risk patients exhibited significantly enhanced CD8⁺ T cell and cytotoxic gene scores, correlating with better responses to chemotherapy and immunotherapy. CIPS inversely correlated with tumor-mutation burden, BRCA1/2 mutations and homologous-recombination deficiency. Single-cell analysis localized signature genes to T lymphocyte and myeloid compartments and linked elevated CIPS activity to augmented intercellular communication in platinum-resistant tumors.</p> Conclusion <p>CIPS captures a CD8⁺ T cell activation program that powerfully stratifies late-stage HGSOC, forecasts therapeutic benefit and offers a practicable biomarker for personalized immuno-oncology strategies.</p>