Cotton is one of the important oil crops, and it is great significance for screening and identification of breeding materials to establish a method of the rapid, nondestructive testing of cotton seed oil content. In this study, near-infrared diffuse reflection spectroscopy of 118 high and low oil materials were adopted to establish models for fast nondestructive determining oil content of cottonseed using near infrared spectroscopy (NIR). One hundred and six cottonseed samples as calibration set that covered the range of seed oil content for upland cotton were used in this experiment. The spectral data of cottonseed were processed using the first derivative and multiplicative scatter correction (MSC). The correction NIR model of oil content was built based on partial least squares (PLS) method with the spectral regions 5 446～8 848 cm-1 and main components (5). The determination coefficient (R2) of calibration model was 0.975, standard error of calibration (SEC) was 0.67. The authors test the model’s actual ability to predict using external validation set. The correlation coefficient (r) of predicted values and the chemistry value was 0.978, the range of prediction error was 0.1%～1.7%. The model established has good predictability. The oil content of 784 breeding stocks were predicted by NIR model, statistical analysis of predictable results elucidated that the NIR model of oil content developed can be well applied to selective breeding and oil related study in cotton.