<h4>Objective</h4>This study aimed to investigate the feasibility and potential value of predictive models for human epidermal growth factor receptor 2 (HER2)-positive status in breast cancer (BC) based on radiomics features from conventional ultrasound images and machine learning models.<h4>Methods</h4>Ultrasound images of 437 patients with surgically and pathologically confirmed BC were retrospectively analyzed, including 144 HER2-positive and 293 HER2-negative cases, which were used as a training and validation dataset. The gene discussed is ERBB2; the disease is breast cancer.