This paper develops an approach to welfare measurement from random utility models (RUMs) that conditions on an individual's observed choice. The economic and statistical properties of the proposed conditional approach to welfare measurement are compared with the unconditional approaches developed by Small and Rosen 35] and Hanemann 16], and a subsample of the 1994 National Survey of Recreation and the Environment (NSRE) is used to illustrate its empirical implications. Conditional and unconditional welfare estimates for two policy scenarios and four repeated discrete choice specifications (e.g., Caulkins 10], Morey, Rowe, and Watson 28]) are presented. These estimates suggest that: 1) sample means of conditional and unconditional welfare estimates are qualitatively similar but often diverge by more a correctly specified model would predict; 2) the conditional estimates appear to be more robust across alternative model specifications; and 3) the distribution of benefits implied by the conditional and unconditional estimates are qualitatively different.