Building façades play a significant role in the thermal and energy performance of a building. The presence of thermal anomalies in façades can cause uncontrolled heat leakages, which impacts a façade's thermal performance. Unmanned aerial vehicles (UAVs) equipped with infrared (IR) cameras are becoming increasingly popular as non-destructive methods for the inspection of thermal anomalies in building envelopes. However, the thermal anomalies identified in UAV-captured images are difficult to localize on a 3D building model, which impedes the assessment and documentation of the thermal anomalies with their properties. This paper proposes a computational workflow to automatically register the detected imagery thermal anomalies to a 3D building model. First, IR images and thermal anomalies are sequentially aligned with the corresponding visual RGB images and mapped into façade reference images (RIs) by using image matching techniques. They are then registered to the 3D building coordinate system through a predefined coordinate transformation process. A pilot case study is presented to demonstrate the processing of UAV-images using the proposed method. As a result of this study, the proposed method enables automated registration and data fusion of UAV-captured images, as well as thermal anomaly information into a 3D building model, supporting the assessment of anomalies and evaluation of existing façade conditions.