Hazardous materials encountered during building renovation or demolition processes not only result in uncertainty in cost estimation and the lead time but also hampers material recyclability and reuse. Therefore, the paper discusses the possibility of predicting the extent of the hazardous materials, including asbestos, PCB, mercury, and CFC, through data mining techniques based on registered records. Pre-demolition audits contain observation data that can be used as a sample for statistical prediction through careful processing. By developing an innovative approach of merging data from environmental inventories with building registers, the positive ratio of remaining hazardous materials in the Gothenburg building stock can be estimated. The study highlights the challenges of creating a training dataset by completing information from the existing environmental inventory, providing new insight into digital protocol development for enhancing material circularity.