We applied near-infrared (NIR) spectroscopy with chemometrics for the rapid and reagent-free analysis of serum urea nitrogen (SUN). The modeling is based on the average effect of multiple sample partitions to achieve parameter selection with stability. A multiparameter optimization platform with Norris derivative filter–partial least squares (Norris-PLS) was developed to select the most suitable mode （d = 2, s = 33, g = 15）T. Using equidistant combination PLS (EC-PLS) with four parameters (initial wavelength I, number of wavelengths N, number of wavelength gaps G and latent variables LV), we performed wavelength screening after eliminating highabsorption wavebands. The optimal EC-PLS parameters were I = 1228 nm, N = 26, G = 16 and LV = 12. The root-mean-square error (SEP), correlation coefficient eRP T for prediction and ratio of performance-to-deviation (RPD) for validation were 1.03 mmol·L^-1, 0.992 and 7.6, respectively. We proposed the wavelength step-by-step phase-out PLS (WSP-PLS) to remove redundant wavelengths in the top 100 EC-PLS models with improved prediction performance. The combination of 19 wavelengths was identified as the optimal model for SUN. The SEP, RP and RPD in validation were 1.01 mmol·L^-1, 0.992 and 7.7, respectively. The prediction effect and wavelength complexity were better than those of EC-PLS. Our results showed that NIR spectroscopy combined with the EC-PLS and WSP-PLS methods enabled the high-precision analysis of SUN. WSP-PLS is a secondary optimization method that can further optimize any wavelength model obtained through other continuous or discrete strategies to establish a simple and better model.