The complexity of modern Engineering projects, driven by the integration of multiple disciplines and the demand for higher system reliability, necessitates advanced methodologies beyond traditional document-based Systems Engineering. Model-Based Systems Engineering ((MBSE)) has emerged as a crucial methodology, leveraging domain models to manage the intricacies of complex Engineering Systems. This review provides a comprehensive analysis of (MBSE), tracing its historical development, key concepts, and theoretical frameworks. It contrasts (MBSE) with traditional Systems Engineering, highlighting its superiority in managing complexity through enhanced traceability, validation, and early detection of design flaws. The application of (MBSE) across industries such as aerospace, automotive, and defense is examined, with a focus on case studies demonstrating its success and the challenges encountered. Emerging trends, including the integration of artificial intelligence, the Internet of Things, and digital twins, are explored, revealing the potential for these technologies to further enhance (MBSE) practices. Despite its strengths, (MBSE) faces challenges related to scalability, integration with other Engineering disciplines, and the need for more robust validation methods. The review concludes with recommendations for practitioners and researchers, emphasizing the importance of continued innovation and education in (MBSE) to address these challenges and ensure its relevance in future complex Engineering projects.