〔Abstract〕 ObjectiveTo explore the value of nomogrambased on DCE-MRI radiomics combined with clinical-radiological featuresin predicting HR status in breast cancer with Her-2 low expression. MethodsA total of 198 patients of Her-2 low expression breast cancerwho underwent standardized breast MRI in our hospital from January 2019 to February 2025 were retrospectively analyzed. Patients were divided into HR (+) group ( n=137) and HR (-) group ( n=61). The cases were divided into a training set (138 cases) and a testing set (50 cases) in a 7:3 ratio.Clinical-radiological model was based on clinical and traditional radiological features,radiomics modelwas based on DCE-MRI, and combined modelwas constructed, respectively. The nomogram was drawn, andreceiver operating characteristic curve was used to compare the performance of different models in predicting HR status. Results The Radiomics score (Radscore) between the HR (+) group and the HR (-) group showed statistical differences inboth the training and testing sets (both P<0.001). The AUC of the clinical-radiological model based on lesion mobility, Ki67, TIC type, enhancement pattern and maximum diameterfor predicting HR status in the training set and testing set were 0.643 and 0.616, respectively. The AUC of the radiomics model in the training set and testing set were 0.897 and 0.860, respectively. The nomogram drawn by combining clinical-radiological features and Radscore showed better predictive performance in both the training set (AUC=0.913) and testing set (AUC=0.898) than the clinical-radiological model (all P<0.05). ConclusionThe nomogramcombinedby DCE-MRIradiomics and clinical-radiological features can effectively predict HR status of breast cancer with low Her-2 expression, which is helpful to the building of individualized treatment plan for breast cancer patients.