Target expansion is a pointing facilitation technique where the users target, typically an interface widget, is dynamically enlarged to speed pointing in interfaces. However, with densely packed (tiled) arrangements of widgets, interfaces cannot expand all potential targets; they must, instead, predict the user’s desired target. As a result, mispredictions will occur which may disrupt the pointing task. In this paper, we present a model describing the cost/benefit of expanding multiple targets using the probability distribution of a given predictor. Using our model, we demonstrate how the model can be used to infer the accuracy required by target prediction techniques. The results of this work are another step toward pointing facilitation techniques that allow users to outperform Fitts’ Law in realistic pointing tasks. Author Keywords Pointing, target expansion, Fitts’ Law, tiled widgets, human performance ACM Classification Keywords H5.m. Information interfaces and presentati...