A two-sided matching method with probabilistic linguistic term sets is proposed based on the BWM (best-worst method), the DEMATEL (decision making trial and evaluation laboratory), and the TODIM, to solve the product service modules matching problem with probabilistic language information considering its interaction and the psychological behavior of decision makers. Firstly, the weight of modules is determined using the BWM and the DEMATEL with probabilistic linguistic term sets. Then, the total dominance degree of product service modules is calculated based on the TODIM to obtain the satisfied matrix. Furthermore, a multi-objective optimization model is constructed to maximize the utility of products and services, which is converted into a single-objective model using the linear weighting method. Finally, an example of the new energy vehicle is provided to prove the effectiveness and feasibility of the proposed method, providing a new direction for the integrated development of new energy vehicle products and services.