The provided is a Soft-sensing method for dioxin emissions of MSWI process based on ensemble T-S fuzzy regression tree. The highly toxic pollutant dioxins (DXN) generated in the municipal solid waste incineration (MSWI) process based on a grate furnace is a key environment index for realizing operation optimization control of the process. The method comprises the following steps: firstly, constructing a dioxin emission TSFRT model based on a screening layer and a fuzzy reasoning layer; then, a plurality of parameter updating learning algorithms aiming at the fuzzy reasoning antecedent part and the fuzzy reasoning consequent part are provided, and five dioxin emission TSFRT models including TSFRT-I, TSFRT-II, TSFRT-III, TSFRT-IV and TSFRT-V are obtained; finally, by taking the dioxin emission TSFRT-III model as an example, constructing an integrated TSFRT (EnTSFRT) model taking the TSFRT-III as a base learner so as to realize high-precision modeling of the dioxin emission concentration.