Digital Twins (DTs) hold promise for the effective implementation of predictive maintenance (PdM) in constructed facilities. However, their adoption in the AECO industry is lagging due to the low level of knowledge on their design and implementation, influenced by the lack of real-world exemplars. This paper presents two real-world BIM-based DTs for PdM in an existing building, detailing the methodology for their design and implementation. The two DT designs cover sensor data integration from legacy systems with digital models of the facility and the programming of analytics for PdM as well as data modeling for representing the physical objects in the digital model. In addition, the paper evaluates the two DT solutions and provides key considerations to make when deciding whether to build or buy. Overall, the study makes contributions towards criteria for DT platform selection, “build versus buy” comparisons, system architecture design, and end-user feedback on DT user interactions and task-dependent performance.