System Dynamics (SD) applications in high volume production operations is ubiquitous, helping to define decision rules to reduce costs associated with the variance in planning orders and inventory. The exploitation of SD in engineer-to-order (ETO) project-oriented supply chains, e.g., in construction, shipbuilding, and capital goods, is less well established. Hence, this research reviews papers which take a systematic ETO perspective modelling construction project, exploiting SD approaches. To comprehensively identify and filter previously published papers, we use a keyword searching method using Web of Science and Scopus databases. After applying relevant exclusion criteria, 145 papers are finally selected. While there have been previous reviews of ETO literature more generally, this paper contributes to the body of knowledge by specifically reviewing SD applications in ETO industries and providing insights by creating a categorization system by which to determine where existing gaps reside. Papers are categorized into the classic four phases of a project: aggregated planning, pre-project planning, project execution, and post-delivery phase. Analyses of the methods, attributes and applications of SD are undertaken for each phase. Findings indicate that SD research covers the range of ETO industries of which construction is the most dominant, demonstrating SD's high applicability. The wealth of case-orientated research in the construction field provides a solid foundation for further SD studies in the ETO field. Further research should focus on 1) developing a general ETO archetype used for performance benchmarking and strategy development in construction projects, 2) introducing analytical tools, such as control theoretic approaches as found in manufacturing production planning and control design, to improve understanding of the ETO systems' dynamic behaviors, and 3) developing cross-phase, cross-project, design production integrated, aggregated planning models via hybrid techniques modelling, which can contribute to a better understanding of an ETO system's performance.