["Transactions in GIS, Volume 30, Issue 4, June 2026. ", "\nABSTRACT\nThe integration of Building Information Models (BIM) and Geospatial Information Systems (GIS) is important to designing and developing smart cities and digital twins. Although significant advancements have been achieved, challenges remain in georeferencing BIM models to integrate them into the geospatial environment. This paper proposes an automated approach for georeferencing architectural BIM models of single buildings using shape geometry matching of building footprints. Our methodology identifies the optimal footprint match for the BIM model using existing datasets of georeferenced building footprints and calculates the transformation matrix for georeferencing the BIM model. Based on the transformation matrix results, we extract the required georeferencing information according to the defined levels of georeferencing in the Industry Foundation Classes (IFC) data format (LoGeoRef 10–50) and populate this data into the BIM models. The experimental results demonstrate that the proposed method achieves high spatial accuracy, with RMSE values consistently below 0.5 m across all test cases and outperforming the Iterative Closest Point (ICP) method in 7 out of 10 cases in terms of RMSE. The proposed method achieved a Top‐1 recognition accuracy of 100%, correctly identifying the corresponding geospatial footprint as the highest‐ranked match for all BIM cases, outperforming the Fourier Descriptor (FD) method (70% Top‐1 accuracy) and the Turning Function (TF) method (60% Top‐1 accuracy) in terms of ranking consistency. The resulting georeferenced BIM models not only ensure consistency but also significantly advance the integration of BIM and GIS, facilitating the development of smart cities and digital twins.\n"]