A spectrophotometer is a scientific instrument used to separate and measure spectral components of biochemical compounds and molecules, which are related to the amount of light intensity absorbed by the substance. The Spectrometric system consists of a light source, optical lenses, monochromators, and detectors. The monochromators are required to separate optical wavelengths using refraction through a prism or diffraction through a diffraction grating. In this paper, the authors demonstrate a novel curve-fitting algorithm based on particle swarm optimization (PSO) for fitting a spectral response with 5 Gaussian distributions. There are 15 variables in total describing the Gaussian equations. To demonstrate the capability of the proposed algorithm, the spectra of samples including the DI water, ethanol, FeCl_2, and the plasmonic gold sensor were collected by UV/Visible spectrophotometer operated with SP-8001 of Metertech for testing the PSO algorithm. As a result, the Gaussian functions based on the PSO model showed the most predictive and well-fitting with the plasmonic gold sensor where the spectrum matched to the single peak at 527.44 nm with 0.9987 R². The peak performed specific modeling equations of peaks and valleys related to its spectral nature mostly using in plasmonic applications.