Built environments contribute significantly to mitigating climate change. However, existing buildings, which form most urban infrastructures, do not typically meet contemporary stringent energy efficiency standards. They are naturally continuously deteriorating, making them a continuous negative contributor to their surrounding environments, which keeps getting worse. Therefore, there is a need to develop performance diagnosis frameworks and approaches for accurate Building Energy Model (BEM) simulations to develop impactful retrofitting design solutions that could make existing buildings perform closer to current efficiency measures. This paper reports on research that focuses explicitly on calibrating envelopes of existing BEMs using drones equipped with thermography sensors. The study specifically focuses on the automation of on-the-fly envelope U-value estimations and verification of calibrated envelope BEMs. The paper examines a renovated campus building in Boston, MA., representing material degradation, thermal bridging, and insulation failures using thermal imaging. A BEM is then calibrated, and post-renovation metered and modeled wintertime heating energy are compared. Goodness of fit measures showcase BEM performance improvement from 21.8%to 0.9%, which demonstrates the utility of the proposed framework. Further research is recommended to expand the focus on anomalies in the envelope and increase the scope from the building scale to the neighborhood scale.