Objective: The primary aim was to assess the feasibility of robotic OSB repair in a preclinical high-fidelity training model, documenting the learning curve and ensuring quality control among surgeons. Design: The learning curve was assessed using the cumulative summation test (LC-CUSUM). Following LC-CUSUM, six additional experiments were performed for competency-cumulative summation (C-CUSUM) analysis to ensure ongoing quality control. Setting: The simulator was created through 3D printing and hand sculpting, simulating a partially exteriorized uterus for laparotomy-assisted laparoscopic OSB surgery. It included a silicone uterus, placenta, and fetal manikin with a simulated OSB lesion, replicating the lesion sac, paraspinal muscles, and neural placode. Population: Four surgeons participated: an expert MFM consultant (TVM), a neurosurgical consultant (AK), an MFM fellow (novice 1, YK), and a neurosurgical resident (novice 2, CK). Methods: The surgical procedure included 8 steps: uterine access, working space creation, lesion exposition, junctional zone dissection, skin mobilization, dural patch application, and closure of myofascial flaps and skin. Success was defined by precise restoration (suture interval <3mm), total operative time ≤180 minutes, and a GEARS score >21/30. Main outcomes: Learning curve and competency were documented via LC-CUSUM and C-CUSUM. Results: Competence was achieved after 15–21 procedures, with novices reaching competency within this range. Participants maintained high performance in subsequent quality-controlled procedures. Conclusion: Robotic-assisted fetal OSB surgery in a high-fidelity simulation is feasible, showing promising outcomes for a large animal model and clinical translation .