The purpose of the study is to test the methods of and to evaluate the effects of a proposed parametric modelling approach to developing the individual tree model in BIM software for the full lifecycle application. Current tree models can't utilize many benefits of BIM, such as clash detection, scheduling, and quantity-take-off. We experiment with a parametric approach towards estimating the shape and growth of trees in a BIM environment with different levels of LoD (Level of Detail). The selected envelope model allows for a description of a wide range of crown forms, including asymmetric forms for existing trees and symmetric forms for planned trees. It also includes the growth function with specific parameters for overall height, height of clear stem, largest crown diameter, height of largest crown diameter, length, and depth of root, and helps calculate the shapes and volumes in time (age), while describing the morphological traits of a tree specific to its inherent species characteristics. Apart from the geometry of the model, we define the information required in each design stage and lifecycle phase as a consistent parameter set based on our proposed modelling approach, attempt to standardize for landscape BIM elements. The proposed envelope model, function, and parameter sets are shown to be effective. We implemented a set of Revit families, including generic models, and a list of species used for teaching in higher education in Switzerland. We successfully performed clash detection, connected to assets for real time visualization, and validated the proposed parameter set by demonstrating the use of the model during the construction phase and handover of the Digital Twin to GIS. The parametric tree object is an important element in the development of BIM for landscape architects and contractors. It ensures that designers, contractors, suppliers, and clients can use the same object across the entire life cycle for the project. Parametric trees will create a better link between the BIM model and the building environment, and give us the possibility to create intelligent facility management models, also known as digital twin.