Welcome to the OSF landing page for what we have affectionately called the idiographic prediction project. Some key links: - Preregistration: https://osf.io/4nm5p - Preprint: https://psyarxiv.com/syhw5 - Open materials on GitHub: https://github.com/emoriebeck/behavior-prediction - Rendered Results: https://emoriebeck.github.io/behavior-prediction/ - R shiny webapp: https://emoriebeck.shinyapps.io/behavior-prediction/ Questions or concerns? Email emorie_beck@northwestern.edu or DM [@EmorieBeck][1] on Twitter. **Abstract**: A longstanding goal of psychology is to predict the things people do, but tools to predict accurately future behaviors remain elusive. In the present study, we used intensive longitudinal data (N = 104; total assessments = 5,971) and three machine learning approaches to investigate the degree to which two behaviors – loneliness and procrastination – could be predicted from psychological (i.e. personality and affective states), situational (i.e. objective situations and psychological situation cues), and time (i.e. trends, diurnal cycles, time of day, and day of the week) phenomena from an idiographic, person-centered perspective. Rather than pitting persons against situations, such an approach allows psychological phenomena, situations, and time to jointly inform prediction. We find (1) a striking degree of accuracy across participants, (2) that a majority of participants models are best informed by both person and situation features, and (3) that the most important features vary greatly across people. [1]: https://twitter.com/emoriebeck