The problem of soil heavy metal pollution has always attracted attention. Therefore, many results have been achieved in this field by the research on the use of hyperspectral remote sensing, mainly focusing on predicting heavy metal content in soil using conventional methods such as derivative of soil spectra and continuous continuum removal. The soil spectral data showed tremendous similarity with non-linear non-stationary mechatronic signals, medical signals, etc. In this study, HHT was used to analyze the soil’s lead (Pb) pollution experimental spectra in the frequency domain. The purpose of the HHT analysis was to achieve the HHT identification of soil’s Pb pollution spectra, and establish the model for predicting Pb content in soil. Firstly, the soil Pb pollution experiment was conducted to collect the spectrum, water content, and organic matter content of soil Pb-contaminated samples. Secondly, the HHT time-frequency analysis and the second derivative of the instantaneous frequency of the second intrinsic mode function (IMF2) component of the Pb pollution spectra of soil samples were used to identify the characteristic bands of soil Pb contamination. Finally, the prediction model of soil Pb content that the parameters were appropriate frequency domain parameters, soil first-order derivative, soil organic matter content, and soil water content was established using boxplot, cluster analysis, and partial least squares. The results showed that HHT time-frequency analysis charts of soil Pb-contaminated could identify soil Pb contamination spectra. There was no abnormal signal in the band sequence between 250 and 430 from HHT time-frequency analysis plots of uncontaminated soil spectrum. There were many abnormal signals in the band between 250 and 430 from soil spectral HHT time-frequency analysis plots under Pb contamination, and with the increase of the concentration, the abnormal signal distribution range became wider and wider. When the pollution concentration reached 800 μg·g-1, a strong abnormal signal was obtained in the band sequence of 270 and the frequency before 0.3 Hz. The mutation of second derivative of IMF2 instantaneous frequency of uncontaminated soil spectrum was very weak after the EMD, while there were obvious mutation points of Pb-contaminated soil spectrum. The characteristic wavelength band of soil Pb-contaminated soil spectrum was 2 150~2 300 nm according to the mutation points and second derivative of IMF2 instantaneous frequency of Pb-contaminated soil spectrum. Six groups of abnormal samples were removed from boxplot based on Hilbert energy spectrum peaks, EMD energy entropy, first derivative, organic matter and water content under different Pb concentrations. Then the Pb-contaminated soil samplings were divided into two categories by cluster analysis. Finally, Hilbert energy spectrum peak, EMD energy entropy, spectral first derivative of 2 134, 790, 1 276 and 2 482 band, organic matter and water content were used as parameters. The BC-PLSR (Boxplot Cluster-Partial Least Squares Regression) models for the data of two categories were established to predict Pb content in soil. The accuracy of the validated model was high, and the correlation coefficients were 0.88 and 0.99, respectively.