To improve the accuracy and efficiency of highway budgeting estimation has been an important research focus in the industry and is the objective of this paper. Useful data were extracted from the Texas Department of Transportation (TxDOT) to develop an alternative to achieve the research objective. Heuristic simulation models pertaining to highway bridge replacement projects were developed to guide engineers to reduce estimation variability before the beginning of planning authorization. The proposed simulation models include independent, correlated, and Latin Hypercube sampling approaches that specifically consider major work items, roll-up work items, and project-level engineering contingency. The charts of cumulative density functions (CDFs) are derived as a handy tool for decision makers to consider project finance initiation, project risk and uncertainty assessment. The systematic procedure can be expanded to other project types and to develop lane-km (lane-mile) cost distributions when ample historical project data are available.