The growing demand for aesthetic orthodontic solutions and the increasing clinical use of clear aligners have created a need for robust digital methods that improve production efficiency and assist clinicians in defining accurate aligner boundaries. This study presents a practical method for determining the trimming paths of clear digital orthodontic aligners by iteratively detecting gingival margin lines on three-dimensional dental models. The proposed approach integrates pose adjustment, curvature estimation, and clustering to delineate gingival margins, which are critical for precise aligner manufacturing and patient comfort. Principal-curvature-based filtering is first employed to identify candidate gingival margin vertices, followed by clustering to remove spurious regions with similar curvature patterns on the crown and gingival surfaces. An iterative contour approach scheme then refines the candidate trimming paths by projecting an initial enclosing contour, derived from a statistical analysis of multiple tooth models, onto each 3D dental model under different approach rates. Experiments on multiple tooth models demonstrate that the proposed method consistently generates clinically acceptable trimming paths and exhibits adaptability across various dental morphologies. Parametric analysis shows that an acceleration term between 0.4 and 0.6 yields stable contour shrinkage, minimizes path misalignment, and enhances smoothness, thereby improving aligner retention and patient comfort. The proposed framework provides a practical, reproducible solution for the digital generation of trimming paths for invisible orthodontic aligners, supporting high-quality aligner production and enabling quantitative assessment of gingival margins in digital dentistry workflows.