Economic evaluations must use appropriate costing methods. However, in multicentre cost-effectiveness analyses (CEA) a fundamental issue of how best to measure and analyse unit costs has been neglected. Multicentre CEA commonly take the mean unit cost from a national database, such as NHS reference costs. This approach does not recognise that unit costs vary across centres and are unavailable in some centres. This paper proposes the use of multiple imputation (MI) to predict those centre-specific unit costs that are not available, while recognising the statistical uncertainty surrounding this imputation.We illustrate MI with a CEA of a multicentre randomised trial (1014 patients, 60 centres), implemented using multilevel modelling. We use MI to derive centre-specific unit costs, based on centre characteristics including average casemix, and compare this to using mean NHS reference costs. In this case study, using MI unit costs rather than mean reference costs led to less heterogeneity across centres, more precise estimates of incremental cost, but similar estimates of incremental cost-effectiveness.We conclude that using MI to predict unit costs can preserve correlations, maximise the use of available data, and, when combined with multilevel modelling is an appropriate method for recognising the statistical uncertainty in multicentre CEA.