The Architecture and Supplier Identification Tool (ASIT) is a design support tool, which enables identification of the most suitable architectures and suppliers in early stages of complex systems design, with consideration of overall requirements satisfaction and uncertainty. During uncertainty estimation, several types of uncertainties that are essential in early design (i.e., uncertainty of modules due to new technology integration, compatibility between modules, and supplier performance uncertainty) have been considered in ASIT. However, it remains unclear whether uncertainty due to expert estimation should be taken into account. From one perspective, expert estimation uncertainty may significantly influence the overall uncertainty, since early complex systems design greatly depends on expert estimation; whereas an opposing perspective argues that expert estimation uncertainty should be neglected given its relatively much smaller scale. In order to understand how expert estimation uncertainty influences the architecture and supplier identification, a comprehensive study of possible modeling approaches has been discussed within the context of ASIT; type-1 fuzzy sets and 2-tuple fuzzy linguistic representation are selected to integrate subjective uncertainty into ASIT. A powertrain design case is used to compare results between cases considering subjective uncertainty versus cases not considering subjective uncertainty. Finally, implications of considering subjective uncertainty in early conceptual design are discussed.