Background: Neo-adjuvant chemotherapy (NaCT) facilitates complete surgical resection in locally advanced, ER+, HER2- breast cancer. Due to its association with improved outcome, pathologic complete response (pCR) to NaCT treatment has been accepted as a surrogate for long-term outcome in clinical trials of patients with HER2+, triple-negative, or luminal B breast cancer. However, only 7-10% of patients with ER+, HER2- disease who receive NaCT achieve pCR. Biomarkers predictive of NaCT response would facilitate patient stratification and enable individualized therapeutic strategies. Here we evaluated the ability of two prognostic biomarker assays to predict NaCT response in ER+, HER2- breast cancer by means of a microarray-based in silico analysis. Methods: Expression and corresponding clinical data associated with pre-treatment biopsies obtained from patients with breast cancer who subsequently received NaCT were obtained from public datasets (GSE entries 16716, 20271, 25066, 32646, 41656, 41998). ER+, HER2- samples were selected based on available immunohistochemistry (IHC) data. The 12-gene molecular score (12-MS) and 21-gene recurrence score (21-RS) were approximated in silico according to published algorithms using expression means of array probes corresponding to the respective genes. Association with pCR was tested by logistic regression with adjustment for cohort. Results: A total of 764 patients with ER+, HER2- disease had available IHC data; 59 experienced pCR (response rate 8%). 12-MS and 21-RS were moderately well correlated (0.71). Both scores were predictive of pCR (12-MS p = 6.9x10^-5; 21-RS p = 0.0023). In bivariate analysis the 12-MS remained a significant predictor of response (p = 0.01) while the 21-RS did not (p = 0.73). Conclusions: In this microarray-based in silico analysis, 12-MS was highly predictive of ER+, HER2- response to NaCT. Optimal stratification of patients with ER+, HER2- breast cancer for NaCT offers the opportunity to individualize care, improve response rates, and possibly avoid ineffective treatment.