This chapter details methods for handling missing data in health economic evaluations, focusing on cost-effectiveness analyses of randomised controlled trials. It explores different types of missingness (MCAR, MAR, MNAR), outlining the implications of each for analysis. The chapter then compares ad-hoc methods (case deletion, single imputation) with statistically principled methods (multiple imputation, fully Bayesian approaches). A case study using the Ten Top Tips trial illustrates multiple imputation and Bayesian techniques, including sensitivity analyses to assess the robustness of results under varying missing data assumptions. The Bayesian approach is explored extensively using JAGS within R.