Effectiveness of Finite Element Modelling in Maxillofacial Surgery: A Review of Evidence from Saudi Arabia

Finite Element Analysis (FEA) is a biomechanical simulation tool in surgical planning, but its adoption and methodological quality vary geographically, as a focused analysis of its application in Saudi Arabia is lacking. This review synthesized and evaluated the methodological rigor, biomechanical insights, and translational relevance of Saudi-based studies employing FEA in maxillofacial surgery. A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and a registered International Prospective Register of Systematic Reviews (PROSPERO) protocol. Databases were searched for studies with affiliation to Saudi Arabia. Methodological quality and risk of bias were assessed using a bespoke tool based on the FEA best practice. Certainty of evidence was evaluated using a modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Three eligible studies covered diverse applications, including mandibular reconstruction, orthognathic surgery, and cranioplasty. Quality assessment revealed methodological heterogeneity, as all studies used patient-specific or anatomically accurate models, but critical best practices have been inconsistently applied. Only one study reported a mesh convergence analysis, while none of the studies performed an experimental validation of their FEA biomechanical predictions. The overall risk of bias was rated moderate to high. Certainty of evidence for any biomechanical outcome was very low according to GRADE. Saudi-based FEA research on maxillofacial surgery is sparse and methodologically nascent. Although technical capabilities in model generation exist, critical gaps in numerical verification (mesh convergence) and experimental validation limit the reliability and translational potential of the findings, underscoring the need to establish standardized, high-quality research protocols to advance data-driven surgical planning in Saudi Arabia.