Prognosis plays a vital role in patient management and decision making. The assessment of prognostic factors, which relate baseline clinical and experimental covariables to outcomes, is one of the major objectives in clinical research. Historically, the impetus for the identification of prognostic factors has been the need to accurately estimate the effect of treatment adjusting for these variables. In oncology, the variability in outcome may be related to prognostic factors rather than to differences in treatments. In this article, we begin with a brief review of prognostic factors, and then subsequently offer a general discussion of their importance. Next, we describe the significance of study design before presenting various modeling approaches for identifying these factors and discussing the relative values of the different approaches. We illustrate the concepts within the framework of published and ongoing phase III trials in oncology.