We present a 'random ray' model to describe Yes/No reaction times (RTs) and errors in perceptual experiments. The ray model is analogous to a random walk, but it is computationally simpler, requiring only elementary geometry. Ray parameters control the drift rates to the Yes and No decision boundaries, bias, and a termination or 'time-out' rule. Rays are normally distributed, but predicted RT distributions are skewed by projection onto the boundaries. Model parameters can be estimated directly from the 16th, 50th, and 84th percentiles of the RT distributions on hit, correct rejection, false alarm, and miss trials, if the data satisfy three easily testable constraints. Examples are given from visual search and object recognition.