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Piéron's Law describes a psychophysical regularity between mean response times and stimulus intensity in signal detection tasks. In this paper we extend this notion to perceptual two-choice decision-making, and demonstrate that Piéron's Law holds as the discriminability between two competing choices is manipulated. We present a Bayesian ideal observer model that explains why a Piéron-like regularity is found when stimulus discriminability is manipulated, and discuss how this model can be extended to cover signal detection tasks.