Numerous workflows exist to computationally generate three-dimensional tree models which effectively simulate their real-world counterparts. This research hybridizes several existing and new approaches to tree modeling to improve growth models based on point cloud data. The digital tree models are created in Blender using an add-on called The Grove, enabling digital trees to grow according to light availability, with full control over their branching structure and form. These three-dimensional tree models are then measured and their dimensions compared to the point cloud counterparts, with average values indicating that the digitally-grown trees are relatively similar to the point cloud trees though smaller in most dimensions. The results demonstrate that point-cloud models of trees can be used to improve computational tree growth models leading to improved tree visualization.