Models can be used in almost any domain for purposes including prediction, inference, or simply describing data. In all these cases, the predictive capacity of a model can be used to evaluate it, and we can build better, more useful models by adhering to good statistical practice. The tidymodels framework harmonizes the heterogeneous model interfaces in R and offers a consistent, flexible framework for modeling suitable for beginners as well as the very experienced. This book provides a practical introduction to how to use R software to create models, focusing on a dialect of the R programming language called the tidyverse. Software that adopts tidyverse principles shares a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. The tidymodels framework for modeling is built to be easily understood and used by a broad range of people.