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The soft-sensing technique of oxygen content in flue gases based on data fusion is presented according to the high first cost of conventional oxygen content analyzers, their high maintenance expenses and low durability. Through the mechanism analysis and the statistical analysis of a number of data, soft-sensing models of oxygen content and air flow. etc. are set up. Based on multisensor data fusion, more reliable and accurate values of input data are obtained. At last, this soft-sensing model fit well with the practical oxygen content, which is illustrated by the simulations.