# Predictive 3D Modeling of Orthognathic Surgery Outcomes Using Machine Learning Algorithms: A Systematic Review: -

**Authors:** Masoud Hasanzade, Ailar Yousefbeigi, Soheil Jafari, OmidReza Veshveshadi, Milad Soleimani, Meysam Mohammadikhah, Seyed Mohammad Mahdi Mirmohammadi

PMC · DOI: 10.31661/gmj.vi.4014 · 2025-11-08

## TL;DR

This paper reviews how machine learning and 3D modeling are being used to predict outcomes of jaw surgery, showing their growing role in improving surgical planning.

## Contribution

A systematic review of recent studies applying machine learning algorithms to 3D modeling for predicting orthognathic surgery outcomes.

## Key findings

- 12 studies using machine learning algorithms like deep neural networks and random forest were identified.
- Most studies used 3D facial models or CBCT images for preoperative design and outcome prediction.
- AI and 3D modeling are increasingly transforming maxillofacial surgical care.

## Abstract

Orthognathic surgery is one of the main corrective treatments in patients
with maxillofacial deformities, performed for functional or aesthetic
reasons. The aim of this systematic review is to examine and analyze studies
published between 2020 and 2025 on the use of machine learning algorithms in
3D modeling to predict orthognathic surgery outcomes.

This study is a systematic review of articles published between 2021 and
2025. To find relevant articles, the Google Scholar and PubMed databases
were searched. The reference lists of relevant articles were also manually
checked to ensure comprehensiveness of the search. Inclusion criteria for
the systematic review were original studies published between 2020 and 2025,
studies that used machine learning or deep learning algorithms to predict
orthognathic surgery outcomes using 3D modeling, articles published in
English, and studies with access to the full text of the article.

A total of 42 articles were identified. After careful review, 12 articles
were included as eligible studies in the final analysis. The flow chart of
study selection in PRISMA format is provided. All studies used machine
learning algorithms such as deep neural networks, reinforcement learning,
random forest, or graph-based models to predict orthognathic surgery
outcomes. Most studies used 3D facial models or CBCT images for preoperative
design and prediction of postoperative outcomes. All studies were assessed
based on quality criteria.

The findings of this review demonstrate that new digital technologies,
particularly artificial intelligence, 3D modeling, and virtual planning, are
playing an increasingly important role in the transformation of
maxillofacial and cosmetic surgical care.

## Full-text entities

- **Diseases:** maxillofacial deformities (MESH:D008446)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12894813/full.md

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Source: https://tomesphere.com/paper/PMC12894813