A method for detecting the arsenic in crayfish rapidly was proposed in this study. The selective adsorbing resin (SQ-407) was placed in 100 mL arsenic standard solution (100 μg/L)， and the adsorption conditions were optimized. Furthermore， fresh crayfish was freeze-dried and digested by microwave， then the digestion solution is adsorbed by SQ-407 under optimized adsorption conditions. The near-infrared spectra of SQ-407 absorbed resin was collected and optimized by using different spectral pretreatment methods (first derivative spectrophotometry， 1st； standard normal variable transformation， SNV； multiplicative scatter correction， MSC； wavelet transform， WT). Partial least squares (PLS) method was used to establish a quantitate model. The arsenic predicted by the established model was compared with the standard method to evaluate the prediction accuracy of the model. Compared to other conditions， the adsorption rate of arsenic was higher(99.30%) at pH 7.0 and 40 ℃ for 90 min. Model constructed by the spectra preprocessed by 1st have shown higher accuracy: the root mean square error (RMSECV) of the training set and the correlation coefficient (R) was 0.033 and 0.995， respectively； the root mean square error (RMSEP) of the prediction set and the correlation coefficient(R) was 0.032 and 0.995， respectively. The results indicated that combining near-infrared spectroscopy with resin adsorption may provide accurate and rapid method for arsenic assessment in crayfish.