Intraoperative margin assessment is needed to reduce the re-excision rate of breast-conserving surgery. One possibility is optical palpation, a tactile imaging technique that maps stress (force applied across the tissue surface) as an indicator of tissue stiffness. Images (optical palpograms) are generated by compressing a transparent silicone layer on the tissue and measuring the layer deformation using optical coherence tomography (OCT). This paper reports, for the first time, the diagnostic accuracy of optical palpation in identifying tumor within 1 mm of the excised specimen boundary using an automated classifier. Optical palpograms from 154 regions of interest (ROIs) from 71 excised tumor specimens were obtained. An automated classifier was constructed to predict the ROI margin status by first choosing a circle diameter, then searching for a location within the ROI where the circle was ≥ 75% filled with high stress (indicating a positive margin). A range of circle diameters and stress thresholds, as well as the impact of filtering out non-dense tissue regions, were tested. Sensitivity and specificity were calculated by comparing the automated classifier results with the true margin status, determined from co-registered histology. 83.3% sensitivity and 86.2% specificity were achieved, compared to 69.0% sensitivity and 79.0% specificity obtained with OCT alone on the same dataset using human readers. Representative optical palpograms show that positive margins containing a range of cancer types tend to exhibit higher stress compared to negative margins. These results demonstrate the potential of optical palpation for margin assessment.