A mathematical model based on statistical decision theory has been devised to represent the human auditory localization task. The known localization cues have been represented as Gaussian random variables, so that their interaction in a given experiment can be analyzed (and predicted) along the lines of classical detection/estimation theory. We have applied this technique to most of the horizontal and vertical localization experiments reported in the literature during the past ten years, encompassing over 200 subjects and 20 000 trials. Using a nonlinear regression program we have been able to estimate the standard deviations of four of the auditory localization cues, allowing objective comparison of their relative accuracy. The resulting model provides a relatively good fit to the published results on 40 localization experiments.Subject Classification: [43]65.62, [43]65.58, [43]65.35.