Coefficient of determination(R²) is most popular criteria for model selection in linear regression model since it is easy to use and also explain how much proportion the candidate mode can accounts among total amount of variation in data. In linear mixed effects model, however, it is not only easy to extend definition of R² but also it is hard to interpret since variation could be defined in various ways. This article provides brief review on several different coefficients of determination proposed for linear mixed effects model. We provides detailed review on the definition and estimation methods for two extended coefficient of determinations which are based on decomposition of total variation and conditional prediction, Also we demonstrate how to use and interpret different coefficients of determination for linear mixed effects model by providing real data example from national physical test 100 project.