In many ecological research studies, abundance data are skewed and contain more zeros than might be expected. Often, the aim is to model abundance in terms of covariates, and to estimate expected abundance for a given set of covariate values. An approach that has been advocated recently involves the use of a conditional model. This allows one to separately model presence and abundance given presence, which should lead to a more complete understanding as to how the covariates influence abundance. The focus of this article is on the calculation of confidence intervals for expected abundance given particular values of the covariates. The standard Wald confidence interval is symmetric, and therefore unlikely to be of much use for skewed data, where reliable confidence intervals for abundance will generally be asymmetric. The purpose of this article is to show how to calculate a profile likelihood confidence interval for expected abundance using a conditional model.