Much recent research interest has focused on handling uncertainty in cost-effectiveness analysis and in particular the calculation of confidence intervals for incremental cost-effectiveness ratios (ICERs). Problems of interpretation when ICERs are negative have led to two important and related developments: the use of the net-benefit statistic and the presentation of uncertainty in cost-effectiveness analysis using acceptability curves. However, neither of these developments directly addresses the problem that decision-makers are constrained by a fixed-budget and may not be able to fund new, more expensive interventions, even if they have been shown to represent good value for money. In response to this limitation, the authors introduce the ‘affordability curve’ which reflects the probability that a programme is affordable for a wide range of threshold budgets. The authors argue that the joint probability an intervention is affordable and cost-effective is more useful for decision-making since it captures both dimensions of the decision problem faced by those responsible for health service budgets. Copyright © 2001 John Wiley & Sons, Ltd.