Amelia II is a comprehensive R package designed for multiple imputation of missing data. It implements an innovative expectation-maximization with bootstrapping (EMB) algorithm that is faster, more flexible, and easier to use than Markov chain Monte Carlo (MCMC) approaches, while providing similar results. The package allows researchers to incorporate Bayesian priors on individual cell values, enhancing the accuracy and robustness of imputations. It supports various data types, including cross-sectional, time-series, and time-series cross-section datasets, and includes graphical diagnostics for model evaluation. Amelia II offers both command-line and graphical user interface (GUI) options, making it accessible to users with varying levels of R expertise. The package is available for Windows, Mac OS X, and Linux, and requires R version 2.10.0 or higher. The article provides a detailed guide on how to use Amelia II, including data preparation, imputation, and analysis, with examples and step-by-step instructions.Amelia II is a comprehensive R package designed for multiple imputation of missing data. It implements an innovative expectation-maximization with bootstrapping (EMB) algorithm that is faster, more flexible, and easier to use than Markov chain Monte Carlo (MCMC) approaches, while providing similar results. The package allows researchers to incorporate Bayesian priors on individual cell values, enhancing the accuracy and robustness of imputations. It supports various data types, including cross-sectional, time-series, and time-series cross-section datasets, and includes graphical diagnostics for model evaluation. Amelia II offers both command-line and graphical user interface (GUI) options, making it accessible to users with varying levels of R expertise. The package is available for Windows, Mac OS X, and Linux, and requires R version 2.10.0 or higher. The article provides a detailed guide on how to use Amelia II, including data preparation, imputation, and analysis, with examples and step-by-step instructions.