3D vegetation models can visually express the spatial structure of plants and have been widely used in urban information modeling, urban ecological environment assessment, urban planning, and resource management. Existing 3D vegetation modeling methods include 3D reconstruction and parametric modeling. However, due to the complexity of plant branches and leaves, the current 3D modeling process cannot simulate tree growth with the influence of different environmental factors. In this study, we proposed a plant growth simulation and analysis method, which is responsive to environmental factors such as gravity, lighting, shading, and the interaction between plants, by using Blender and The Grove plugin. Then, by selecting Fangcaoyuan Garden at Daijiahu Park in Wuhan, China, as a case study based on the park's construction documents and field research data, the plant models were generated in 3 growing stages: initial stage, growing stage, and mature stage. By comparing with the on-site LiDAR-scanned model, the 3D spatial IoU of the generated model was 61%, showing that the simulation results are generally acceptable. We also proposed a method to calculate the LAI, LAD, biomass, and carbon storage values based on the generated vegetation model to illustrate and predict the ecological indicators of the plants. This study can provide a reference for plant growth simulation and ecological indicators analysis with generated high-realistic vegetation models.