The present empirical work investigates the emergence of psychological and subjective well-being profiles by means of multivariate analysis, specifically hierarchical and k-means clustering. The study utilized a general framework based on systems theory and a person-centered approach, which draws from the work of Shmotkin (2005) and Busseri et al. (2009). The study employed a representative sample of 32,944 cases drawn from the self-reported well-being module of the National Institute of Statistics and Geography of Mexico. The findings revealed the presence of five clusters of well-being that are consistent with those previously identified in the literature. The well-being profiles demonstrate differential behaviors across the variables of well-being and domains of life satisfaction, thus highlighting the systemic behaviors of interdependence, nonlinearity, and stability within the profiles. Finally, the contribution of this work to well-being research, specifically from a systemic and person-centered approach, is discussed.