Therapeutic responses of non-small cell lung cancer (NSCLC) to epidermal growth factor receptor (EGFR) - tyrosine kinase inhibitors (TKIs) are known to be associated with EGFR mutations. However, a proportion of NSCLCs carrying EGFR mutations still progress on EGFR-TKI underlining the imperfect correlation. Structure-function-based approaches have recently been reported to perform better in retrospectively predicting patient outcomes following EGFR-TKI treatment than exon-based method. Here, we develop a multicolor fluorescence-activated cell sorting (FACS) with an EGFR-TKI-based fluorogenic probe (HX103) to profile active-EGFR in tumors. HX103-based FACS shows an overall agreement with gene mutations of 82.6%, sensitivity of 81.8% and specificity of 83.3% for discriminating EGFR-activating mutations from wild-type in surgical specimens from NSCLC patients. We then translate HX103 to the clinical studies for prediction of EGFR-TKI sensitivity. When integrating computed tomography imaging with HX103-based FACS, we find a high correlation between EGFR-TKI therapy response and probe labeling. These studies demonstrate HX103-based FACS provides a high predictive performance for response to EGFR-TKI, suggesting the potential utility of an EGFR-TKI-based probe in precision medicine trials to stratify NSCLC patients for EGFR-TKI treatment.