Abstract This model proposes a multidimensional probabilistic model to assess romantic compatibility among industrial and professional populations in India. Drawing upon neurochemical typology (Fisher 2009), attachment theory (Bowlby 1988), conflict resolution frameworks (Thomas and Kilmann 1974), assortative mating principles (Watson et al. 2004), and the theory of second best (Lipsey and Lancaster 1956), the model integrates ten dimensions: neurochemistry, attachment style, conflict style, cognitive aptitude, age differential, income aggregation, mutual attraction, sexual temperament, dominance orientation, and kink openness. Each dimension is operationalized on a standardized 0–10 scale and assigned a temporally evolving weight reflecting changes in relational priorities over a ten-year horizon. Compatibility is computed as a weighted aggregation of these scores, further adjusted by a penalty factor when red-flag incompatibilities are detected. The model incorporates fuzzy logic (Zadeh 1965) to represent the graded and uncertain nature of relational attributes, enabling compatibility to be expressed both numerically and linguistically. A correlation matrix among dimensions is specified to account for interdependencies, and a neural network-based approach is proposed for future weight remodeling. This framework offers a comprehensive, theoretically grounded methodology for evaluating relational fit in high-cognition Indian populations. Limitations include reliance on self-reported data, cultural specificity, and simplification of complex constructs into numeric indices. Future research directions include longitudinal validation and integration of machine learning approaches to enhance predictive accuracy.