This paper extends the behavioral results reported in Fischer et al. (2000) by developing amodel addressing preference uncertainty in multiattribute evaluation. The model is motivatedby two hypotheses regarding properties of multiattribute profiles that lead to greater preferenceuncertainty. Our attribute conflict hypothesis predicts that greater within-alternativeconflict (discrepancy among the attributes of an alternative) leads to more extremity (veryhigh or low attribute values) leads to less preference uncertainty. To provide a deeperexplanation of attribute conflict and extremity effects, we develop RandMAU, a family ofadditive (RandAUF) and multiplicative (RandMUF) random weights multiattribute utilitymodels. In RandMAU models, preference uncertainty is represented as random variation inboth the weighting parameters governing trade-offs among attributes and the curvatureparamters governing single-attribute evaluations. Simulation results show that RandMAUsuccessfully predicts both the attribute conflict and attribute extremity effects exhibited bythe experimental participants in Fischer et al. (2000). It also predicts an outcome valueeffect on error whose form depends on the shape of single-attribute functions and on thetype of multi-attribute combination rule.