We present a model of enumeration that demonstrates one possible explanation for the limited capacity of subitizing. This analytical approach can be contrasted with most previous research on subitizing which has been primarily descriptive in nature, and which has tended to assume a structural limitation on the phenomenon. Our simulation results suggest instead that the limitation may arise from the functional constraints of learning to optimize among enumeration strategies for a space whose combinatorics increase greatly with number.