<p>Traditional classification of traumatic brain injury (TBI) has relied predominantly on neurological responsiveness, most notably the Glasgow Coma Scale, to stratify injury severity. While this approach has provided a common clinical language for decades, it inadequately captures the biological heterogeneity, anatomical variability, and contextual factors that shape injury trajectories and outcomes. Growing recognition of these limitations has prompted the development of multidimensional classification frameworks, including the clinical, biomarker, imaging, and modifier (CBI-M) model, designed to reflect the complex and dynamic nature of TBI. The objective is to describe a structured, implementation-science-based methodology for transitioning from traditional TBI classification to the CBI-M framework while preserving clinical continuity, data integrity, and system feasibility. We propose a phased transition methodology grounded in implementation science principles, emphasizing backward compatibility, additive integration, reproducibility, scalability, and distributed responsibility. The methodology is organized into three sequential phases: (I) mapping legacy classification elements to CBI-M domains to ensure conceptual continuity; (II) operational integration through workflow-aligned, staged adoption across the trauma care continuum; and (III) system-level embedding via electronic medical records, trauma registries, governance structures, and continuous evaluation mechanisms. Explicit attention is given to data stewardship, accountability, and longitudinal consistency. The proposed methodology provides a practical roadmap for embedding multidimensional TBI classification into routine clinical practice without disrupting existing workflows or registries. By aligning classification domains with established clinical roles and care phases, the approach minimizes documentation burden while enabling incremental adoption on the basis of institutional readiness. Governance and audit mechanisms support fidelity, comparability, and sustainability over time. Transitioning to multidimensional TBI classification requires more than conceptual validity; it demands deliberate implementation strategy. The proposed methodology offers a scalable, system-aware pathway for integrating the CBI-M framework into real-world trauma care, supporting precision-oriented classification while maintaining continuity with legacy systems. This approach provides a foundation for durable adoption, quality improvement, and future research in traumatic brain injury.</p> Graphical Abstract <p></p>