Advance knowledge of the time required by an observer to detect a target visually is of interest, e.g., in preparing flight scenarios, in modeling mission performance, in evaluating camouflage effectiveness, and in visual-scene generator calibration. A wide range of computational models has therefore been developed to predict human visual search and detection performance. This study is performed to test the quality of the predictions of three of these models: ORACLE, Visdet, and a formula by Travnikova. The three different models are used to predict the results of an experiment in which observers searched for military vehicles in complex rural scenes. The models predict either the mean time required to find the target, or the probability of finding the target after a given amount of time, from a few physical parameters describing the scene (the mean scene luminance, the angular dimensions of the field of view and the target, the intrinsic target contrast, etc.). None of the models reliably predicts observer performance for most of the scenes used in this study. ORACLE and Visdet both overestimate the detection probability for most situations. The formula by Travnikova does not apply to the scenes used here.