Structural equation modeling (SEM) represents an efficacious data analysis instrument for the investigation of family business phenomena. It is an appropriate methodology for conducting research on management, organizational, and financial reporting data. A substantial body of research has been conducted to compare and contrast the two principal forms of SEM: covariance-based (CB) and partial least squares (PLS). This research aims to delineate the conditions and standards for applying these two methodologies. There is a paucity of knowledge regarding researchers' comprehension of and adherence to the principles of definition, data collection, scale utilization, measurement model, and bias in the family business SEM design process. This paper provides an overview of the quality of coverage of these cornerstones in journal articles using SEM in family business research published in journals registered in the Scopus database up to 2023. A total of 61 articles that employed SEM methodology were subjected to analysis using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model. The analysis provides an overview of the journals that published the relevant articles (49), the keywords and co-authorships used, and the details and shortcomings of the methodologies used. The overview of the studies found to be relevant revealed an urgent need for researchers to apply methodological elements related to the design of SEM studies in a more consistent and uniform manner. Additionally, research gaps were identified that may be relevant for researchers to implement novel analyses using both PLS and CB formats.