We assessed how much, if anything, people would pay for a laboratory test that predicted their future disease status. A questionnaire was administered via an internet-based survey to a random sample of adult U.S. respondents. Each respondent answered questions about two different scenarios, each of which specified: one of four randomly selected diseases (Alzheimer’s, arthritis, breast cancer, or prostate cancer); an ex ante risk of developing the disease (randomly designated 10% or 25%); and test accuracy (randomly designated perfect or “not perfectly accurate”). Willingness to pay (WTP) was elicited with a double-bounded, dichotomous-choice approach. Of 2,223 respondents who completed the survey, most (70-88%, depending on the scenario) were inclined to take the test. WTP was lower for Alzheimer’s and higher for prostate cancer compared with arthritis, and rose somewhat with disease prevalence and for the perfect vs. imperfect test. Median WTP varied from $109 for the imperfect arthritis test to $263 for the perfect prostate cancer test. Respondents’ preferences for predictive testing, even in the absence of direct treatment consequences, reflected health and non-health related factors, and suggests that conventional cost-effectiveness analyses may underestimate the value of testing.