In response to the rapid advancement of auto-refractor technology, most optometry shops provide refraction services. Despite their speed and convenience, the measurement values provided by auto-refractors include a significant degree of error due to psychological and physical factors. Therefore, there is a need for repetitive testing to obtain a smaller mean error value. However, even repetitive testing itself might not be sufficient to ensure accurate measurements. Therefore, research on a method of measurement that can complement auto-refractor measurements and provide confirmation of refraction results needs to be conducted. The customized optometry model described herein can satisfy the above requirements. From the existing optical technologies, using human eye measurement devices to obtain individual relevant optical feature parameters is no longer difficult. These parameters allow us to construct an optometry model for individual eyeballs. They also allow us to compute spot diagrams produced from the optometry model using the CODE V macro programming language before recognizing the geometrical spot diagram with the back-propagation neural network algorithm to obtain the accurate refractive diopter. Results show that the accuracy achieved was above 98% and that this application could significantly enhance the service quality of refraction.