Although chemistry is a well-known, sought-after interpersonal phenomenon, it has remained relatively unexplored in the psychological literature. The purpose of this article is to begin articulating a theoretically grounded and precise definition of interpersonal chemistry. To that end, we propose a conceptual model of interpersonal chemistry centered around the notion that when two or more individuals experience chemistry with one another, they experience their interaction as something more than the sum of their separate contributions. Our model stipulates that chemistry encompasses both behavior (i.e., what chemistry "looks like") and its perception (i.e., what it "feels like"). The behavior involves interaction sequences in which synchronicity is high and in which people's goals are expressed and responded to in supportive and encouraging ways. The perception of chemistry includes cognitive (i.e., perception of shared identity), affective (i.e., positive affect and attraction), and behavioral (i.e., perceived goal-relevant coordination) components. We review existing research on chemistry as well as supporting evidence from relevant topics (e.g., attraction, similarity, perceived partner responsiveness, synchrony) that inform and support this model. We hope that this conceptual model stimulates research to identify the circumstances in which chemistry arises and the processes by which it affects individuals, their interactions, and their relationships.

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner's ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person's own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.