A subset of early stage estrogen receptor (ER)-positive breast cancers considered "high risk" for recurrence with endocrine therapy alone by current genomic prognostic predictors, such as Oncotype DX, is no longer high risk after receiving adjuvant chemotherapy. We hypothesized that a recently described gene expression-based outcome predictor adjuvant chemotherapy and endocrine therapy sensitivity (ACES) could re-stratify these patients into high and low risk groups for relapse when treated with both chemo- and endocrine therapies. ACES involves four separate modules (endocrine sensitivity, chemotherapy sensitivity, chemotherapy resistance, and survival prediction) that yield a prediction for good or poor outcome with current standard of care multimodality therapy. ACES was applied to Affymetrix gene expression data from 2 retrospectively collected ER-positive and HER2-negative patient cohorts that were uniformly treated with adjuvant endocrine and chemotherapy (n = 250). Each sample was first risk stratified by a genomic surrogate of Oncotype DX, and the high risk patients (n = 76) were re-stratified by ACES. Recurrence-free survival (RFS) was evaluated with ACES risk categories. The Oncotype DX high risk but ACES good prognosis patients (n = 24, 32%) had an RFS of 95% compared to 76% in the poor prognosis group (n = 52; log-rank p = 0.033) at 5 years. ACES risk category remained an independent predictor in multivariate analysis after adjusting for age, T-stage, and lymph node involvement at diagnosis (hazard ratio 0.15; p = 0.072). Tertiary risk prediction that takes into account chemotherapy and endocrine sensitivity, and baseline prognosis may help identify high risk ER-positive patients who have excellent survival after chemotherapy.