BACKGROUND: A proportion of breast patients achieve axillary pathological complete response (pCR) following NAC. However, few studies have investigated the potential of quantitative parameters derived from dual-energy CT (DECT) for predicting axillary lymph node (ALN) downstaging after NAC. METHODS: This study included a prospective training and retrospective validation cohort from December 2019 to June 2022. Both groups enrolled invasive breast cancer with biopsy-proved metastatic ALNs who underwent contrast-enhanced DECT and NAC followed by surgery. A metastatic ALN, named target lymph node (TLN), was marked with metal clip at baseline. Quantitative DECT parameters and size of TLN, and clinical information were compared between pCR and non-pCR node group referring to postoperative pathology. Three predictive models, clinical, quantitative CT, and combinational models, were built by logistic regression and nomogram was drawn accordingly. The performance was evaluated by the receiver operator characteristic curve and clinical usefulness was assessed by decision curve analysis. RESULTS: A total of 75 and 53 patients were included in training and validation cohort respectively. Of them, 34 (45.3%) and 22 (41.5%) patients achieved nodal pCR in the two sets. Multivariable analyses revealed that negative estrogen receptor expression, parenchyma thickness and the iodine concentration of TLN at post-NAC CT were independently predictive factors for pCR. The combinational model showed discriminatory power than the single clinical model (AUC, 0.724; p = 0.003) and quantitative CT model (AUC, 0.728; p = 0.030) with AUC of 0.847 and 0.828 in training and validation cohort. It provided enhanced net benefits within a wide range of threshold probabilities. CONCLUSION: Quantitative DECT parameters can be used to evaluate axillary nodal status after NAC and guide personalized treatment strategies.