FELICITAS revolutionizes the way we think about preferences, skills, and other latent personal attributes (PSAs), estimates their heterogeneity along with its determinants, and provides policy implications. PSAs are key drivers of a myriad of decisions which combine to create an individual’s life story. Differences in PSAs, together with constraints and luck, underlie inequalities in outcomes. Knowledge of PSAs is essential for policymakers to design effective public policy. Self-knowledge of PSAs is crucial for individuals to sort into occupations, activities, and relationships which enable them to flourish. However, unobserved PSAs are only noisily revealed by observed behavior. I develop a decision model which separately identifies noise due to imperfect self-knowledge and endogenous effort. I quantify their respective roles in different choice settings, de-bias estimates of PSAs, and assess their importance in essential life outcomes. I use these insights, along with an innovative discrete choice framework in which respondents choose between pairs of realistic life stories, to provide causal estimates of distributions in preferences (valuations) for policy-relevant life outcomes (longevity, health, family structure) in the United States and in Europe. I link the estimated heterogeneity to culture, demographics, and other PSAs. Finally, I examine a new latent personal attribute - an individual's propensity to perceive time in a distorted manner. In a twist to received wisdom that time flows faster when one is engaged in a more enjoyable activity, I propose that utility obtained from an activity can be inferred using differences between “felt” and elapsed time. I conjecture that the perceived duration of a task may both be the relevant decision variable, which reflects an individual's exerted effort on a task, and a determinant of required hourly wages. If empirically validated, we obtain a cardinal measure of utility which will transform its measurement.