unburned carbon content of fly ash is an important index reflecting the combustion efficiency of utility boiler. Measuring the carbon content in the fly ash accurately is beneficial to the detection and adjustment of boiler combustion. This paper uses the ant colony neural network which optimized the initializing weights, thresholds and numbers of node in hidden layer of BP neural network. The optimized neural network is used to predict the unburned carbon content of fly ash. And the prediction result is also analyzed in this paper.