Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66-0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China's crop cultivation were estimated to be 194 Gg N2O-N with a 95% confidence interval of 180-208 Gg N2O-N in the year 2016.