Forests play an important role in providing timber, storing carbon, and supporting wildlife. To understand how trees grow and respond to the environment, researchers need detailed information about tree shape and size. In this study, we used a special 3D laser scanning tool, similar to a camera that sees depth, to measure the structure of pine trees in Florida without cutting them down. We tested several computer methods to separate the leafy parts from the woody parts in the scans and found that more accurate separation leads to better tree models. These models help us estimate important tree features like trunk size, number of branches, and branch angles. We found that using advanced machine learning methods produced the most reliable results, though simpler methods also worked well for certain tree types. This research helps improve our ability to track tree growth and forest changes over time, which is important for managing forests and understanding how they respond to climate change.