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Based on the data of leaf spectrum and Cu2+ content in corn leaves under different Cu2+ stress gradients, the intrinsic mode function (IMF) of leaf spectrum under different stress gradients was obtained by empirical mode decomposition (EMD), and IMF4 was selected for HHT envelope analysis. The variation trend and pollution degree of Hilbert envelope spectrum of maize leaves under different Cu2+ stress gradients were studied. The peak index of envelope spectrum (E1) and envelope spectral kurtosis coefficient (E2) were constructed to analyze the envelope spectrum changes of leaves under different Cu2+ pollution levels. The correlation analysis and stepwise regression statistics between the characteristic parameters of envelope spectrum and the content of Cu2+ in leaves were also carried out to establish a single and double variable prediction model of Cu2+ content in maize leaves. The experimental results showed that the spectral envelope of corn leaves under different concentrations of Cu2+ stress was a continuum within 100Hz frequency;values of E1 and E2 showed a positive correlation with the Cu2+ content in leaves. The characteristic parameter values of two envelope spectra all reached the maximum at the Cu(150) position, since both E1 and E2 values had a good correlation with the content of Cu2+ in leaves, E1 and E2 can be used as predictors for monitoring heavy metal pollution in maize plants. According to the application results of Cu2+ content prediction model constructed by E1 and E2 single and double variables, it was proved that the bivariate model constructed by E1 and E2 had the best predictive ability.