This dissertation investigates how people make inferences about missing information.Whereas most prior literature focuses on how people process known information, I show that the extent to which people make inferences about missing information impacts judgments and choices. Specifically, I investigate how (1) awareness of known unknowns affects overconfidence in judgment in Chapter 1, (2) beliefs about the knowability of unknowns impacts investment strategies in Chapter 2, and (3) inferences about forgotten unknowns influence choices from memory in Chapter 3.Chapter 1 investigates how overconfidence can stem from neglecting to consider missing information. Most prior research has attributed overconfidence to people focusing disproportionately on evidence favoring the chosen hypothesis relative to its alternatives. In this iii chapter, I find that neglecting unknown evidence independently contributes to overconfidence. In a first study, respondents answered questions such as, "Which of these fast food items has more calories, a Subway sandwich, or a McDonald's cheeseburger? / How confident are you?" Using a process tracing technique, I found that participants who considered more missing evidence were less overconfident than those that thought about more known evidence. Meanwhile, participants who considered more unknown information answered the same number of questions correctly, resulting in better calibration. In two additional studies, I prompted participants to list unknowns before assessing confidence in their judgments. This "consider the unknowns" technique reduced overconfidence substantially, and was more effective than the de-biasing technique most often prescribed in the research literature ("consider the alternative"). Importantly, considering the unknowns was selective in its impact: it reduced confidence only in domains where participants were overconfident, but did not affect confidence in domains where participants were wellcalibrated or under-confident.Chapter 2 investigates how inferences about the knowability of missing information impacts investment choices. Recent research has found that people intuitively distinguish aleatory uncertainty that is inherently random or stochastic (e.g. What is the probability that a fair coin will land heads?) from epistemic uncertainty that is attributed to missing knowledge or information (e.g., Which company had a larger market capitalization at the end of 2015, Google or Apple?). In a series of surveys and experiments involving laypeople, experienced investors, and financial advisors, I found that investors who viewed stock market uncertainty as more epistemic/knowable searched for more stock information and were willing to pay more for financial advice, whereas investors who viewed stock market uncertainty as more aleatory/random diversify more. Similarly, when investors were primed to think about epistemic iv uncertainty they are more willing to pay for stock information whereas when they were primed to think about aleatory uncertainty they diversified mo...