Accurate prediction of construction project completion costs remains a critical challenge, as a substantial share of projects experience cost overruns. Recent advances in data-driven modeling and emerging technologies have expanded the methodological options available for both point and range estimation. This study synthesizes insights from a literature review, two machine-learning–based estimation models developed by the authors, and a focus group interview with industry experts to evaluate the relative efficacy of single-value versus range-based forecasting. To contextualize these technical findings within real-world decision environments, a focus group interview was conducted with experienced construction professionals. Results indicate a strong preference for range-based estimation during planning and risk assessment, while point estimates remain indispensable for contractual and operational contexts. Participants expressed awareness of developing tools but noted limited current adoption. They also emphasized the need for emerging technologies to enhance accuracy, support scenario analysis, and provide flexible outputs suited to different project phases.