The demolition of historic residential buildings generates substantial construction and demolition waste, the effective management of which is essential for advancing circular economy objectives. This study presents a BIM-based waste management framework developed for European residential buildings constructed around the turn of the 19th and 20th centuries, reflecting their characteristic construction methods and material use. The framework employs a predefined structural and material database to automatically quantify waste streams from BIM data at LOD 300. Demolition materials are classified into eight categories consistent with the waste hierarchy: reuse, recycling, energy recovery, and disposal. The model also accounts for the influence of demolition techniques, enabling comparative scenario analysis of recovery outcomes. A Budapest case study demonstrated that selective manual demolition increases the proportion of high-value reuse from 19.6% to 56.8% compared to mechanical demolition, while preserving 88% of salvaged bricks and 90% of architectural stone elements. Although the framework was tested on a building in Budapest, the results are extendable to the wider Central European (Austro-Hungarian) building stock due to typological similarities. The findings confirm the framework’s capacity to support sustainable, circular waste management strategies in historic building demolition.

In the inner areas of large cities, many residential buildings built at the turn of the 19th and 20th centuries remain standing. The maintenance and renovation of these buildings have emerged as critical priorities over recent decades. E.g., in Budapest during the socialist era, the majority of these buildings were not renovated, and maintenance was largely neglected. In the subsequent 10–15 years following the end of socialism, financial resources for renovations were scarce due to the extensive transfer of properties from state to private ownership. It is only in the last decade or so that renovations have begun to be systematically addressed. Consequently, a significant portion of the building stock is still pending renovation. Given the current economic conditions, sustainable maintenance and necessary conversion are of paramount importance. Unfortunately, few standardized condition assessment methods are implemented in industrial practice, and the literature on this topic is limited. To address these challenges, we have developed an algorithm and model for condition assessment and decision support, which we refer to as the Complex Building’s Decision Support System based on Fuzzy Signatures (CBDF system). Our model employs a fuzzy signature-based approach to account for uncertainties, errors, and potentially missing data that may arise during the assessment process. The primary aim of this model is to equip professionals involved in building condition assessment with a tool that enables them to make consistent and objective decisions while minimizing errors. This paper provides a brief overview of the CBDF system and presents test results from the assessment of a selected structural component of a building, demonstrating the system’s functionality.