<p>This study explored the application of near-infrared (NIR) spectroscopy for the rapid and non-destructive determination of macromolecular composition in Spirulina biomass, aiming to support the industrial implementation of this technology in the microalgae industry. Twenty-three Spirulina samples cultivated under varying environmental conditions and photobioreactor designs were analysed to obtain a broad range of protein (38.9–65.8% DW), carbohydrate (6.8–33.7% DW), lipid (4.9–17.5% DW), ash (7.9–35.7% DW), and moisture (0.1–17.9% FW) contents. Standard laboratory analyses were used as reference methods, while NIR spectra were recorded using a Bruker Tango FT-NIR spectrometer. Partial least squares regression models were developed to correlate spectral data with chemical composition. The results demonstrated excellent predictive performance for protein (R² = 0.982; RPD = 7.54) and moisture (R² = 0.971; RPD = 5.93) contents, good performance for carbohydrates and ash (R² = 0.918 and 0.896; RPD = 3.5 and 3.1, respectively), and moderate performance for lipids (R² = 0.714; RPD = 1.87). The high variability among samples due to different cultivation systems enhanced model robustness. These findings confirm the potential of NIR spectroscopy as a fast, cost-effective, and environmentally friendly tool for real-time quality control in the Spirulina production industry.</p>