New ventures often do not correctly foresee real market opportunities or the best way to address them. How to cope with unforeseen, unpredictable factors, also referred to as unknown unknowns, is critical for new ventures. Findings in the fields of innovation and project management have shown that dealing with the unpredictable requires management approaches different from those used for classical plan-and-achieve-the-target projects. Management approaches for novel initiatives include a combination of trial-and-error learning (i.e., flexible redefinition of the new venture business model as new information emerges) and selectionism (i.e., running multiple parallel trials and choosing the best performing approach ex post). The management approach must be chosen when the venture is set up. This requires a venture management team to diagnose at the outset whether unknown unknowns are present (or possible), although unknown unknowns cannot be identified initially by definition because they emerge over time. Anecdotal testimony from experienced venture managers and project managers suggests they have a feeling for where their knowledge is limited. However, such a claim is controversial. Some researchers think the concept of diagnosing unforeseeable influence factors is an oxymoron. Thus, the research question in this article is this: How can unforeseeable influence factors in a new venture be diagnosed at the outset? Research to date has insufficiently addressed the a priori identification of the type of uncertainty faced by a new venture. Based on models from decision theory, this article suggests dividing the overall problem of structuring the venture into subproblems for which the management team can identify knowledge gaps. Using a case study, the article describes how knowledge gaps were identified for the subareas of a new venture in a real situation and how this diagnosis was used to correctly identify the areas where unknown unknowns lurk. These areas were managed in a different way (i.e., with learning and experimentation) than the other subproblems (i.e., with targets and deadlines). As a result, the venture could successfully respond to unforeseeable events. The results of this study suggest that a decomposition of the overall venture management problem into subproblems is feasible and natural to managers, that a qualitative assessment of knowledge gaps and vulnerability to unknown unknowns is possible, and that a structured, process-like approach can be used to identify subproblems, to determine their uncertainty profiles, and to update the uncertainty profiles. These results are immediately useful to venture management and venture capitalists in setting up the venture's structure for effective response to uncertainty. The results advance research about uncertainty management by offering a systematic set of questions for the diagnosis of unknown unknowns before they can be formally described. The usefulness of this process can be tested further in more formal empirical research.