BACKGROUND AND OBJECTIVES: The training of cerebrovascular neurosurgeons faces significant challenges, particularly due to the decreasing volume of aneurysm clipping procedures. Traditional training methods rely heavily on clinical case availability, which limits skill development. This study aimed to implement and validate a Microsurgical Aneurysm Training Simulator (MATS) that offers a comprehensive, realistic, and cost-effective solution for neurosurgical training. METHODS: MATS was designed using semiautomated algorithms and additive manufacturing to replicate a bifurcation aneurysm of the middle cerebral artery. The simulator includes a pulsatile perfusion system and is compatible with indocyanine-green angiography. The simulation was evaluated by medical students, residents, and experienced neurosurgeons through face, content, and construct validity assessments. Performance was measured using a modified Objective Structured Assessment of Aneurysm Clipping Skills. RESULTS: MATS demonstrated high face and content validity, particularly in replicating the visual and procedural aspects of aneurysm clipping. Participants across all experience levels showed significant improvements in modified Objective Structured Assessment of Aneurysm Clipping Skills scores, with medical students displaying the most pronounced learning curve. The simulators compatibility with indocyanine green angiography was confirmed, though limitations were noted in replicating physiological perfusion pressures and the visual impact of subarachnoid hemorrhage during aneurysm rupture simulations. CONCLUSION: MATS is a validated, cost-effective, and reproducible tool that significantly enhances neurosurgical training by improving technical skills, especially in inexperienced participants. While the simulator effectively mimics key aspects of aneurysm surgery, further research is needed to assess its predictive validity and its potential impact on actual surgical outcomes.