Plastics were widely utilized due to their durability, versatility, and low production cost; however, their increasing production and disposal posed significant environmental and industrial challenges. Accurate identification and characterization of microplastic mixtures were therefore essential for recycling, quality control, and research applications. Conventional analytical methods were often destructive, time-consuming, and unsuitable for rapid, in situ analysis. This study investigated near-infrared (NIR) spectroscopy combined with statistical analysis as a non-destructive approach for evaluating microplastic polyamide (PA) and polystyrene (PS). Wavelength spectra were recorded in the 937–1651 nm range at varying concentrations. Statistical analyses were applied to quantify concentration transmittance relationships and assess classification performance. Transmittance decreased consistently with increasing polymer content, particularly within the 1100–1450 nm region. Optical spectroscopy measurements were compared yielding coefficients of determination of 0.7704 and 0.7275 for PA and PS respectively with statistical significance supporting predictive modelling. Principal Component Analysis (PCA) analysis achieved clear separation of concentration groups. Overall, NIR spectroscopy based on optical transmittance method proved to be a reliable, rapid, and non-destructive method for microplastic characterization, with potential applications in industrial monitoring and quality assurance.