The concept of \(m\)-extended negatively dependent (\(m\)-END, in short) random variables is introduced and the Kolmogorov exponential inequality for \(m\)-END random variables is established. As applications of the Kolmogorov exponential inequality, we further investigate the complete convergence for arrays of rowwise \(m\)-END random variables and the complete consistency for the estimator of nonparametric regression models based on \(m\)-END errors. Our results generalize and improve some known ones for independent random variables and dependent random variables.