Advanced vector autoregression analysis of 41 patients across 1,959 echocardiographic frames reveals that functional mitral regurgitation exhibits distinct beat-to-beat patterns depending on whether it stems from atrial or ventricular dysfunction. Left ventricular volume emerged as the strongest short-term predictor across both subtypes, while left atrial volume showed predictive power at longer time delays. Crucially, papillary muscle dynamics showed striking asymmetry: in ventricular-type regurgitation, muscle length predicted valve leakage, while in atrial-type disease, regurgitation predicted muscle deformation at every measured interval. This temporal framework represents a paradigm shift from traditional static cardiac assessments toward dynamic, patient-specific phenotyping. The methodology could transform personalized treatment strategies for the millions affected by mitral regurgitation, potentially enabling physicians to predict disease progression and optimize interventions based on individual temporal patterns. However, as this preprint awaits peer review, the small sample size of 41 patients limits generalizability, and validation in larger, diverse populations will be essential before clinical implementation.