Background <p>The increased detection of stage I lung adenocarcinoma (LUAD) through low-dose spiral CT highlights the need for better prognostic tools. This study developed an immune-related gene signature to predict outcomes and guide personalized management.</p> Methods <p>Immune-related genes from the ImmPort database were analyzed using univariate Cox and LASSO regression. A multivariate Cox model and nomogram were constructed, with performance evaluated via ROC curves, decision curve analysis, and calibration curves. The model was validated in two independent datasets. Patients were stratified by risk score, followed by differential gene expression, enrichment, and immune infiltration analyses.</p> Results <p>A 29-gene signature was established and validated, showing robust AUC values and clinical utility. Enrichment analysis linked the signature to tumor progression and metastasis. High-risk patients exhibited higher tumor purity and lower immune/stromal scores, indicating an immunosuppressive microenvironment.</p> Conclusion <p>This immune-related gene signature enables risk stratification and supports personalized treatment strategies for stage I LUAD.</p>