In spectrophotometry, mixtures of chemical constituents cannot be determined simultaneously due to spectral interferences as well as the close λmax wavelength, the wavelength at which a substance absorbs the most photons. Since the spectra of individual components in a ternary mixture overlap, determining the concentration of individual components using the wavelength of maximum absorbance, λmax, can lead to a significant error. In this paper, the concentrations of individual components in ternary synthetic mixtures of nitrophenol, aniline, and phenol were estimated simultaneously using a model based on a genetic algorithm and partial least squares. The spectrophotometric data of ternary mixtures with almost identical spectra of nitrobenzene, aniline, and phenol were calibrated using partial least squares modeling without losing prediction capability, and a genetic algorithm method was used to select the appropriate wavelengths for partial least square calibration. The experimental calibration matrix of 27 samples containing a ternary mixture of nitrobenzene (1.0–20.0 mg L−1), aniline (1.0–15.0 mg L−1), and phenol (4.0–18.0 mg L−1) was designed by measuring the absorbance between 200 and 340 nm at a 1 nm wavelength intervals. The model was verified by using six different mixtures with varying concentrations of nitrobenzene, aniline, and phenol. The root mean square error in the prediction of nitrobenzene, aniline, and phenol was 0.1411, 0.1670, and 0.2861 with the genetic algorithm, and 0.3666, 0.6149, and 0.6279 without the genetic algorithm, respectively. This method can be successfully applied to estimate the components in synthetic mixtures accurately. Since this method is accurate and robust, it can be applied to actual industrial wastewater that contains a mixture of toxic chemicals. This eliminates the complications and costs related to separation and purification prior to the analysis using costly chromatographic methods.