The prediction and control of the inner thermal state of a blast furnace, represented as silicon content in blast furnace hot metal, pose a great challenge because of complex chemical reactions and transfer phenomena taking place in blast furnace ironmaking process. In this article, a chaos-based iterated multistep predictor is designed for predicting the silicon content in blast furnace hot metal collected from a pint-sized blast furnace. The reasonable agreement between the predicted values and the observed values indicates that the established high dimensional chaotic predictor can predict the evolvement of silicon series well, which conversely render the strong indication of existing deterministic mechanism ruling the dynamics of complex blast furnace ironmaking process, i.e., a high-dimensional chaotic system is suitable for representing the blast furnace system. The results may serve as guidelines for characterizing blast furnace ironmaking process, an extremely complex but fascinating field, with chaos in the future investigation. (C) 2009 American Institute of Chemical Engineers AIChE J, 55: 947962, 2009