Data-Driven Suspension Diagnostics is a diagnostic methodology within the domain of mechanical system analysis that fundamentally relies on empirical data and statistical learning techniques to identify, monitor, and predict suspension system anomalies, distinguishing it from model-based or rule-based approaches by prioritizing data-derived insights over theoretical or heuristic assumptions.