This is the first reported method for determining the percentage volume particle size distribution of a powder (microcrystalline cellulose) by near-infrared (NIR) reflectance spectroscopy. A total of 113 samples of powdered microcrystalline cellulose were used from six different commercially available grades, with different moisture contents (range: 0.9-4.8% m/m). NIR reflectance measurements of these samples were made in narrow soda glass vials. Reference particle size data for the samples were acquired by laser diffraction. The NIR data were then calibrated to measure particle size by partial least squares regression. The effects of a range of different NIR data pre-treatments on calibration and prediction precision were investigated. Overall, simple absorbance data were found to produce regression models with the best predictive ability (root mean square error of prediction = 0.90%). The method was also found to be insensitive to moisture content.