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Objectives Tooth autotransplantation has gained renewed attention thanks to digital dentistry, but the biomechanics of transplanted teeth remains poorly understood. Finite element (FE) models have shown promise in better understanding the biomechanical risks, but their creation is time-consuming. Model order reduction (MOR) techniques have been used in the medical field to reduce computing time, and this study aimed to develop a reduced model of a transplanted tooth using the Higher-Order Proper Generalized Decomposition method. Methods The FE model of a previous study was used to learn von Mises root stress, and axial and lateral forces between 75 and 175N were used to simulate different occlusions. For the finite element analysis, all dental materials were supposed homogeneous and linearly elastic except for the periodontal ligament that was supposed hyper-elastic. For model order reduction, the procedure follows a two-stage offline-online decomposition. In the offline stage (learning phase), snapshots are generated with high fidelity simulations. In the online stage, the results are interpolated with respect to the model parameters. Results The reduced model's accuracy varied between 0.1 and 5.9%, and lateral forces were less accurate. Using MOR significantly reduced the time required to deliver root stresses by an average of 5.9 hours. Conclusions This study provides a proof of concept for real-time stress values using MOR, accurately capturing the biomechanical behaviour of transplanted teeth while significantly decreasing computing time. Future work may include development of an aid decision system based on real-time simulation of the biomechanics of the transplanted tooth to help dental surgeons decide the best position during the surgery.