There currently exist many methods for 3D plant growth modelling. Both terrestrial laser scanning and UAV use sensors which are great ways to obtain the structural properties of plants. Structural properties such as volume and size of plants are crucial as they are valuable inputs that enable the research of plant growth, specifically on anomalies detection and the effects of before and after pruning. Computational modelling is widely used to simulate various phenomena for different applications. It is a fast and cost-effective way using computational modelling to better understand the cause and effect of pruning certain parts of the tree without having to go on site. Nevertheless, many computer pruning simulation programmes have a fixed plant growth model and do not have many options for user interactions and customization. Therefore, this book chapter proposes a plant pruning simulation utilizing L-Py as a solution that caters to various types of plants suiting users’ needs. Different parameters can be set by the user to customize and conduct pruning on their own tree models. The proposed method can be employed for preliminary analysis and a learning platform for users to understand pruning management.