The analysis object of this paper is a cylindrical pressure shell with a single orthogonally nozzle and reinforcement structures, consisting of a nozzle wall and an insert plate. Taking the non-iteration design process of the reinforcement structures of this cylindrical pressure shell as an example, this paper proposes a non-iteration design method based on the gradient boosting decision tree (GBDT). This work provides a reference for the design of structures without the need of iteration design process. The non-iteration design method proposed in this paper includes three parts: dataset generation, generation of the non-iteration design surrogate model, and development of a dedicated APP for non-iteration design. Firstly, a machine learning dataset is obtained by the parametric finite element analysis through ABAQUS-Python for the reinforcement structures of the cylindrical pressure shell. Then, based on the Gradient Boosting Decision Tree and the multi-output regressor, a non-iteration design surrogate model is generated based on the dataset. Finally, a dedicated forward design APP (HUST-FWD01) is developed to standardize the non-iteration design and verification processes for the reinforcement structures. The results show that the dimensions of the reinforcement structure can be obtained without the need of iteration by the non-iteration design surrogate model, which is generated based on the non-iteration design framework proposed in this paper. In the surrogate model, the maximum stress near the opening of the pressure shell is used as the input, and the dimensions of the reinforcement structures are the outputs. The verification examples show that the errors are all within 3% between model inputs and the FEA results corresponding to model outputs. The research results can provide a design method without the need of iteration for the reinforcement structures of cylindrical pressure shell with a single orthogonally hole as well as the structures akin to them.