Abstract: Disclosed is a method for estimating a blast furnace throat temperature based on a multilayer ore-to-coke ratio distribution model. According to the method, blast furnace equipment parameters and a burden distribution matrix are utilized, the burden layer profile of each layer is calculated according to the burden distribution movement process, a burden layer distribution model is established in combination with the descending process, and the ore-to-coke ratio of each burden layer is obtained. According to the method, the ore-to-coke ratio distribution of multiple layers and main parameters of a blast furnace are used as input, a generalized regression neural network is used for estimating the temperature at the corresponding measurement position of throat temperature, so as to realize the monitoring of throat temperature in the blast furnace process.