  A growing demand for handling uncertainties and risks in performance-driven
building design decision-making has challenged conventional design methods.
Thus, researchers in this field lean towards viable alternatives to using
deterministic design methods, e.g., probabilistic methods. This research
addresses the challenges associated with conventional methods of
performance-driven building design, i.e., ignoring the existing uncertainties
and lacking a systematic framework to incorporate risk assessment in building
performance analysis. This research introduces a framework (BIMProbE) to
integrate BIM-based parametric tools with building probabilistic performance
analysis to facilitate uncertainty analysis and risk assessment in
performance-based building design decision-making. A hypothetical building
design scenario is used to demonstrate the application of the proposed
framework. The results show that the probabilistic method leads to a different
performance ranking order than the deterministic method. Also, the
probabilistic method allows evaluating design options based on different risk
attitudes.
