This talk reviews statistical methods for evaluating heterogeneous treatment effects (HTE) from randomized clinical trials and observational data including subgroup identification and estimation of individualized treatment regimens. We use typology of methods proposed in Lipkovich, Dmitrienko and D’Agostino (2017) and discuss their advantages and disadvantages. A simulated data set is used to illustrate challenges of estimating HTEs.