It is now possible to routinely measure the aberrations of the human eye, but there is as yet no established metric that relates aberrations to visual acuity. A number of metrics have been proposed and evaluated, and some perform well on particular sets of evaluation data. But these metrics are not based on a plausible model of the letter acuity task and may not generalize to other sets of aberrations, other data sets, or to other acuity tasks. Here we provide a model of the acuity task that incorporates optical and neural filtering, neural noise, and an ideal decision rule. The model provides an excellent account of one large set of evaluation data. Several suboptimal rules perform almost as well. A simple metric derived from this model also provides a good account of the data set.