A method for assessing the role of low-level factors in complex tasks is described. The method, which involves comparing simple-discrimination performance and complex-task performance for the same stimuli, was used to assess the role of low-level factors in multiple-fixation visual search. In one experiment, the target and background were composed of line segments that differed in color, orientation, or both; in another, target and background were composed of filtered-noise textures that differed in spatial frequency, orientation, or both. Most of the variance in search time was found to be predictable from the discrimination data, suggesting that low-level factors often play a dominant role in limiting search performance. A signal-detection model is presented that demonstrates how current psychophysical models of visual discrimination might be generalized to obtain a theory that can predict search performance for a wide range of stimulus conditions.