aspg-22-4328-1791483623 20261008182023 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group International Journal of BIM and Engineering Science IJBES 2571-1075 2026 12 2 Ashraf Elhendawi School of Civil Engineering and Built Environment, University of Greater Manchester, Bolton, UK Moustafa Metwally Graduate School of Management (GSM), Management and Science University, Shah Alam, Malaysia Building information modelling is increasingly applied to structure engineering information across the life cycle of built assets, but existing buildings are often underconnected to operational data for retrofit prioritisation. This research proposes a BIM-connected retrofit prioritisation model that converts building-performance information into an engineering information layer for initial screening. The method integrates BIM-aligned feature organisation, transparent machine learning, diagnostic validation, and scenario-driven screening to flag buildings for further assessment by engineers. The paper proposes a workflow for institutions and cities seeking to transition from disparate disclosure records to evidence-based retrofit prioritisation without relying on the immediate availability of digital twins. The results suggest that operational, geometric, and typological features can be used to generate interpretable screening markers that help guide engineering judgement, benchmarking, and incremental retrofit strategies. This research offers a replicable model that supplements, rather than substitutes for, in-depth audit and modelling. 2026 25 31 4328 https://creativecommons.org/licenses/by/4.0/ 10.54216/IJBES.120204 https://www.americaspg.com/journal/22/article/4328 https://www.americaspg.com/storage/articles/manuscripts/01KT6NRM8D7P4BPJ5SD1VTNB1D.pdf