A new preoperative nomogram approach aims to reduce unnecessary lymph node surgery in hormone receptor-positive, HER2-negative breast cancer by predicting hidden node spread using routine clinical data. The tool was validated and is designed for practical surgical decision support rather than requiring specialized biomarkers. By improving prediction of which patients may benefit from full lymph node evaluation, the strategy could reduce morbidity tied to overtreatment while supporting tighter tailoring of surgical extent. For oncology departments, the operational question is how quickly such models can be embedded into workflow and whether performance holds across centers with differing patient mix and imaging or pathology practices.