Veterans Affairs (VA) provides eye care and vision treatment to all eligible veterans to help improve eye and vision health. Over the past years, timely access to eye care has become a challenge with the increase in its demand. Therefore, it is important to improve the efficiency of the processes by identifying and implementing best practices. The main purpose of this study is to identify critical factors to improve VA’s eye care and vision clinical performance. For this research, VA aggregate data from FY 2017-2019 are collected for Optometry and Ophthalmology Services for multiple medical centers in different regions in the US and analyzed through statistical models including Multiple Linear Regression, Stepwise Regression, and Principal Component Analysis (PCA). 26 different model variations were compared in an experimental setting to see the robustness and sensitivity of the findings. Multiple Linear Regression showed better performance with R-squared values of 0.294, 0.322 and adjusted R-squared 0.264, 0.292 for Optometry and Ophthalmology, from all the tested models respectively. The results indicate that input factors such as "Physician Clinical FTEE", "Clinical Support Staff per Physician Clinical FTEE", "Physician Clinical FTEE per 10KSpecialty Unique" "Adj MDFTEE", "Highest complexity (complex_1a)" and "low complexity (complex_3)" are the most critical factors for Optometry performance. On the other hand, "Residents", "Physician Clinical FTEE", "Physician Clinical FTEE per 10KSpecialty Unique", "Clinical Support Staff per Physician Clinical FTEE" and "seem to be the most critical factors for Ophthalmology performance.