In the most recent Health Risk and Exposure Assessment (HREA) for Ozone, the US Environmental Protection Agency (EPA) used an exposure-response function estimated on clinical data to calculate the risk of lung function decrements in a series of population-level simulations. These risk estimates are subject to both statistical uncertainty (which arises because the exposure-response function was estimated on a sample of clinical observations) and model uncertainty (which arises because there are different plausible ways to model the relationship between ozone exposure and lung function decrement). In this paper, we describe and apply an approach that allows us to estimate the statistical uncertainty present in these risk estimates. In the example we consider, statistical uncertainty produces 95% confidence intervals on the risk estimates that in some cases include zero, suggesting that in these cases we cannot exclude the possibility of no health risk to lung function owing to ozone exposure. Model uncertainty is also apparent, with a plausible alternative model specification leading to a substantially different distribution of risk.