As observations in the past do not necessarily hold into the future, predicting future cancer occurrence is fraught with uncertainty. Nevertheless, predictions can aid health planners in allocating resources and allow scientists to explore the consequence of interventions aimed at reducing the impact of cancer. Simple statistical models have been refined over the past few decades and often provide reasonable predictions when applied to recent trends. Intrinsic to their interpretation, however, is an understanding of the forces that drive time trends. We explain how and why cancer predictions are made, with examples to illustrate the concepts in practice.