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A technique to predict the gas emission from the coalface is presented which is realized by the intrinsic mode SVM modeling on the basis of the intrinsic mode components drawn out from the observed dada by means of the EMD (empirical mode decomposition) method. The intrinsic mode functions, that is, IMF components, are obtained by the EMD analysis of the historical recording dada of gas emission, and after the prediction of each intrinsic mode is carried out by the extrapolation of its regression function determined by the SVM flmction regression approach, then the prediction result of gas emission is derived through the reconstruction summing all prediction results corresponding to different intrinsic modes. From an application example related to the monitoring data it can be seen that the introduction of EMD method into ther theoretical modeling to predict the gas emission from the coalface obviously improves the accuracy in comparison with the conventional SVM method, to have the prediction results agreement with the monitoring data. The theoretical analysis shows that in modeling the gas emission from the coalface, the extraction of intrinsic modes and the operation of SVM method make full use of the sampling data driven adaptive performances, and hence provide better theoretical flmdamentals for guarding perfect prediction efficiency. [ABSTRACT FROM AUTHOR]