This study examined whether automated follicle measurements using AI can predict the number of retrieved and mature oocytes as accurately as traditional manual assessments. Data from IVF cycles across five centers were analyzed, comparing physician-reported measurements with those generated by an AI platform. Both types of data were used in predictive models to estimate oocyte outcomes. Results showed that automated measurements performed comparably to manual reports. This suggests that AI can be a reliable tool for monitoring ovarian stimulation, offering time savings and consistency.