Challenges associated with ensuring the accuracy and reliability of cost estimation of highway bid items, especially during the conceptual phase of a project, are of significant interest to state highway agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. A systematic literature review was performed to determine research trends, identify, categorize the factors influencing highway unit prices, and assess the performance of conceptual cost prediction models. This research proposes a geographic information system (GIS)–based methodology that leverages vast historical bid data for unit-price estimation and the robust GIS capabilities with consideration of the effects of project-specific location and variations due to cost escalation on different bid items. A comparison of the three spatial interpolation techniques operationalized in this research revealed that disjunctive and empirical Bayesian kriging models led to more accurate cost prediction than ordinary kriging algorithms.