The potential of near-infrared spectroscopy (NIRS) for screening the inorganic arsenic (i-As) content in the red crayfish (Procambarus clarkii Girard 1852) was assessed. Sixty-two samples belonging to this species were freeze-dried and scanned by NIRS. The i-As contents of the samples were obtained by acid digestion-solvent extraction followed by hydride generation atomic absorption spectrometry and were regressed against different spectral transformations by modified partial least-squares (MPLS) regression. Second derivative transformation equations of the raw optical data, previously standardized by applying standard normal variate and de-trending algorithms, resulted in a coefficient of determination in the cross-validation (1-VR) of 0.84, indicative of equations of good quantitative information. The standard error of cross-validation to standard deviation ratio, shown by the second derivative equation, was similar to those obtained for other trace metal calibrations reported in NIRS reflectance. Spectral information related to chromophores and lipids of the red crayfish tissues, and also the plant matter contained in their stomachs, were the main organic components used by MPLS for modeling the selected prediction equation. This pioneering use of NIRS to predict the i-As content in red crayfish represents an important savings in time and cost of analysis.