Abstract: With the increasing application of Building Information Modeling (BIM) technology in the engineering field, its potential in enhancing the efficiency of road engineering design, construction, and management has become evident. However, existing Revit-based road-BIM modeling methods are generally plagued by low efficiency, information distortion, and limited model usability. To address these issues, this study takes Section II of the G324 national-highway realignment project between Yaogu and Chadong in Yunfu City as its case study and proposes a high-precision road-BIM modeling approach that integrates a parametric family library, Dynamo visual scripting, and Python-based secondary development. By creating segment-specific parametric families and leveraging Revit’s Dynamo platform together with customized Python scripts, the method realizes fully automated and highly accurate model generation. Compared with conventional manual practices, it increases modeling efficiency by 85% and reduces the error rate of key component information to 0.3%, thereby significantly enhancing model usability. Moreover, the research explores how parametric design can improve model adaptability and flexibility, providing valuable technical insights and practical guidance for the application of BIM technology in similar road-engineering projects.