The integration of AI into dental implantology enhances not only the precision and efficiency of treatment planning and execution but also enables a more tailored approach to patient care. This review explores the potential of machine learning approaches in predicting the success of dental implant procedures.The successful osseointegration of dental implants is a multifactorial process influenced by a wide range of patient-specific and implant-related variables . As the demand for dental implants continues to rise, clinicians are increasingly seeking advanced tools and strategies to enhance treatment predictability, reduce complications such as peri-implant bone loss, infection, and implant failure, and improve long-term outcomes . Recent advancements in machine learning have enabled the development of predictive models capable of analyzing complex patient data to identify critical factors influencing implant success .This innovative technology addresses critical challenges encountered by clinicians during implant identification, treatment planning, and outcome prediction. A key advantage of AI lies in its capacity to predict the likelihood of successful osseointegration and identify potential risk factors associated with implant failure. By serving as a robust decision-support tool, AI enables clinicians to make evidence-based decisions, thereby improving the overall success rates of dental implant therapies. Additionally, AI has demonstrated remarkable efficacy in the early detection of peri-implantitis, a significant concern for the long-term maintenance of dental implants. Nevertheless, despite its considerable promise, the clinical application of AI is not without limitations. Ongoing research and rigorous clinical validation are imperative to ensure the reliability and generalizability of AI models in real-world dental practice. Furthermore, the development of well-curated datasets and advanced AI architectures remains essential, as these foundational components are critical to the successful implementation of AI in dental implantology.

**Diagnosis and Treatment Planning** AI performs analysis of CBCT and radiographs for landmarks and bone density. The virtual planning of the implant optimizes its size, angulation, and position. **Predictive Analytics and Decision Support**   AI predicts the success of an implant based on the patient’s bone quality and systemic health. Automated risk assessment pinpoints high risk patients.   **Surgical Assistance and Navigation**   AI-robotics enhances the accuracy of implant placement using guided assistance. AI-assisted 3D printing enables rapid production of custom implants and surgical guides. **Prosthetic Design and Occlusion Analysis**   AI-assisted CAD/CAM significantly enhances the design of implant-supported prosthesis. AI analyzes the bite force to protect the implant from being overloaded and failing.   **Post-Operative Monitoring and Maintenance**   AI sensors monitor the stability and osseointegration of the implants.   Chatbots and virtual medical assistants offer postoperative care and reminders.   **Research and Innovation**   AI helps in creation of new biomaterials with improved biocompatibility.   Implant success rate clinical research is augmented by machine learning technology.

AI-driven image analysis and deep learning algorithms enhance the precision of implant placement, reducing risks and optimizing aesthetics. Moreover, AI-driven data analytics provide valuable insights into patient-specific treatment strategies, improving overall success rates.AI uses large amounts of data to predict post-surgery complications, treatment responses, and long-term outcomes for oral surgery patients. This helps doctors make timely decisions, allowing for early interventions and personalized follow-up care.