The article introduces the caret package, which simplifies the process of building and tuning predictive models in R. It highlights the package's focus on model training and tuning across various techniques, data preprocessing, variable importance calculation, and model visualizations. The package is designed to handle complex classification and regression models, making it easier to manage the syntactical nuances of different functions. An illustrative example from computational chemistry is used to demonstrate the package's functionality, including data splitting, model building, performance characterization, and parallel processing. The article also discusses methods for handling near zero-variance predictors and multicollinearity, and provides detailed examples of using the train function for model tuning and evaluation. Additionally, it covers the use of parallel processing to reduce training time and the benefits of using multiple processors. The caret package is available on CRAN and can be extended with other packages for additional functionalities.The article introduces the caret package, which simplifies the process of building and tuning predictive models in R. It highlights the package's focus on model training and tuning across various techniques, data preprocessing, variable importance calculation, and model visualizations. The package is designed to handle complex classification and regression models, making it easier to manage the syntactical nuances of different functions. An illustrative example from computational chemistry is used to demonstrate the package's functionality, including data splitting, model building, performance characterization, and parallel processing. The article also discusses methods for handling near zero-variance predictors and multicollinearity, and provides detailed examples of using the train function for model tuning and evaluation. Additionally, it covers the use of parallel processing to reduce training time and the benefits of using multiple processors. The caret package is available on CRAN and can be extended with other packages for additional functionalities.