It can be argued that there is an ethical requirement to classify correctly what is known and what is unknown in decision situations, especially in the context of biomedicine when risks and benefits have to be assessed. This is because other methods for assessing potential harms and benefits, decision logics and/or ethical principles may apply depending on the kind or degree of uncertainty. However, it is necessary to identify and describe the various epistemic states of uncertainty relevant to such estimates (...) in the first place. Therefore, this paper aims to develop a category system of different epistemic states of uncertainty which, although not exclusively, is primarily intended to be applied to early clinical trials. It is formed on the basis—and various combinations—of three dimensions of uncertainty that represent certain parts of incomplete knowledge: outcome (type of event), probability (of outcome) and evaluation (assessment of outcome). Furthermore, it is argued that uncertainty can arise from three different sources (the structure of the object of research, the state of the evidence, or individual handling of the research and already existing knowledge). The categories developed are applied to actual examples from gene therapy and genome editing to illustrate that they can be helpful for a more precise definition of the respective uncertainties, especially in the context of risk–benefit assessment. The categories allow a differentiated perspective of decision-making situations from the point of view of incomplete knowledge in general, but particularly, for example, in early clinical research, and may thereby support a more acceptable ethical assessment of potential harms and benefits. (shrink)