Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM₁₀, NO₂, SO₂, O₃, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R² = 0.9443 and 0.9388, p < 2.2 × 10⁻¹⁶). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO₂ and relative humidity are the factors impacting regional deviations in the prediction model.