INTRODUCTION Breast cancer (BC) is the leading cause of cancer-related death in women. Since the early 1980s, the implementation of screening programs has reduced the number of patients diagnosed with locally advanced breast cancer. Currently, the treatment for these patients involves initial neoadjuvant chemotherapy (NACT) followed by surgical treatment. In recent years, NACT has also been used for highly chemoresponsive tumors such as triple-negative (TN) and HER2-positive (HER2+) breast cancer. The widespread use of NACT has led to additional benefits, including downstaging of breast and axillary neoplasms, resulting in reduced morbidity; improved cosmetic outcomes due to increased use of conservative interventions; and personalized adjuvant chemotherapy treatment. Several studies have shown that response to chemotherapy predicts better systemic outcomes. Complete pathological response (pCR), defined as the absence of invasive neoplastic residue in the surgical specimen, has been predictive of better distant outcomes. Limited evidence exists regarding other predictive factors for distant outcomes. Given the significant impact of disease recurrence on patient prognosis, efforts have been made to understand the factors contributing to recurrence and to predict which patients are more prone to relapse. In this context, the term Early Disease Recurrence (EDR) has been coined to define the occurrence of disease recurrence, both locally and distantly, within 3 years after completing treatment. In recent years, the potential of radiomic analysis in aiding diagnostic and therapeutic decision-making processes in BC has been demonstrated. Specifically, radiomic features obtained from Magnetic Resonance Imaging (MRI) images appear capable of predicting tumor receptor status, differentiating tumor subtypes, and predicting response to NACT. Although the role of radiomics in predicting recurrence has been investigated, research is still in its early stages, and there are variations in technology and methodology for extracting radiomic features. Additionally, to date, no studies have evaluated the feasibility and reliability of using radiomic models combined with clinical and radiological variables to predict disease recurrence in BC patients undergoing NACT.