To explore the feasibility of rapid and green determination of chromium (Cr) in rice husk from polluted paddy fields by laser-induced breakdown spectroscopy (LIBS), synergy interval partial least squares (SiPLS) combined with LIBS was employed for a quantitative analysis of Cr in 24 rice husk samples from different polluted paddy fields around a certain lake in Jiangxi Province. The real concentration in samples was determined by atomic absorption spectroscopy (AAS), and it ranged from 32.51 μg/g to 510.33 μg/g. The LIBS profiles of rice husk samples in the range of 422-446 nm were collected and three characteristic spectral lines, Cr I 425.43 nm, Cr I 427.48 nm, and Cr I 428.97 nm, were clear. The spectra from 422 nm to 446 nm were processed by the nine-point smoothing method, and then an optimal model was established with the SiPLS method. The results show that the root mean square error of cross validation and the root mean square error of prediction set were 26.1 μg/g and 22.6 μg/g, respectively, and the correlation coefficients for the training set and the prediction set were 0.9714 and 0.9840, respectively. The relative error was calculated and the T-test was carried out. The results indicate that the average relative error was 6.20% between predicted values from the SiPLS algorithm and real values from AAS, and there is no significant difference. The proposed model has high prediction accuracy, and provides reference for the rapid green determination of heavy metals in natural agricultural products.