ObjectiveThis study aimed to evaluate stress distribution in unilateral maxillary defects using finite element analysis (FEA) to compare subperiosteal (SI) and zygomatic implants (ZI).Materials and methodsA 3D model of a unilaterally atrophied maxilla was reconstructed from CT scans. Five scenarios were simulated: (1) quad zygoma implants (SC1), (2) zygoma and conventional implants (SC2), (3) two-piece SI and conventional implants (SC3), (4) one-piece SI and conventional implants (SC4) and (5) one-piece SI implant (SC5). Mechanical properties were assigned based on data in the literature; a 450 N force for occlusal loading and a 93 N force for oblique loads were applied.ResultsUnder vertical loading, SC2 exhibited the highest tensile stress (Pmax) in the atrophic region (R-AM), while SC4 showed the lowest Pmax across the entire maxilla, indicating better stress distribution. Under oblique forces, SC2 also showed the highest Pmax in R-AM, while SC5 had the lowest Pmax overall. Minimum principal stress (Pmin) followed similar patterns, with SC4 and SC5 demonstrating lower stress levels than the other scenarios. Abutment stresses were highest in SC2 and lowest in SC4. Overall, the SI scenarios (SC3–SC5) exhibited lower stress transmission to the alveolar bone than the ZI scenarios (SC1 and SC2), with SC4 providing the most balanced stress distribution across all regions.ConclusionsSI implants, mainly the one-piece SI (SC4), offered a more favourable stress distribution than ZI implants in unilateral maxillary defects, reducing the risk of excessive bone stress. This finding suggests that SI implants may be superior for such cases, although individual patient anatomy should guide implant selection. Further clinical studies are necessary to confirm these biomechanical findings in vivo.Clinical relevanceThis study underscores the crucial role of implant selection in minimising stress on the alveolar bone in unilateral maxillary defects. Based on these findings, we recommend personalised implant strategies based on biomechanical insights to enhance outcomes in maxillofacial reconstruction.