AbstractCost estimation is critical to a typical transportation project’s development process. Specifically, project owners use cost estimates during the scoping phase to set project budgets for funding approval and cost management. Because of the lack of detailed design, state transportation agency (STA) estimators often rely on the Pareto principle, also known as the 80/20 rule, in early cost estimating by estimating only high-impact work items and roughly calculating the costs of remaining items using a fixed percentage. However, it is a heuristic rule of thumb that does not apply to every scenario. Moreover, STAs’ guidance is minimal, and few studies have investigated the validity of this common practice. This study proposes two novel models that utilize well-established multiobjective optimization methods to automatically determine optimal major work items and necessary related information to apply the items to STAs’ scoping-phase estimating of new projects. A case study was conducted using an STA’s actual historical bid tabulation data for two project work types. The first model’s output shows that 10% and 20% of the work items can respectively contribute up to 92% and 97% of total project cost, and the cost contribution ratios vary with not only project work types but also projects under the same type, with coefficients of variance minimized simultaneously and calculated by the model. Because of the variance, mean or median measures can represent the center of cost percentages for estimating new projects’ total cost from major items’ costs. The second model’s results reveal that using the median is preferred because of lower expected errors. Also, using an optimal 10% item set and the median of its cost contribution ratios in past projects to estimate future projects results in the approach’s expected average error of 8.5%, which is acceptable in the scoping phase.