In this study, we propose a nondestructive method based on hyperspectral imaging technology to determine the bloodstain age. The spectral images of the bloodstains on a white ceramic tile, white paper, and white cotton cloth with different aging times can be obtained using a hyperspectral imager and can be characterized in the spectral range of 550-800 nm. Further, the bloodstain age is predicted using an artificial neural network model. The results indicate that the regression coefficients of the aging time of bloodstains for the three samples are larger than 0.9930 within 30 h under the laboratory conditions. The average root mean square error of prediction (RMSEP) is 18.29 min, and the median relative error δ_M is 8.05%. Thus, the proposed method is observed to be effective for estimating the aging time of the bloodstains in a short time (<30 h).