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Modelling of the Surface Urban Heat Island (SUHI) temporal variations have been a great concern. However, most previous studies only focused on modelling the SUHI variations in the past period, yet those for their future patterns remain rarely investigated. By incorporating various predictable meteorological variables in the SVM regression model, this study achieved an attempt to the prediction for the next-day SUHIs over Chinese main cities. Both the SUHI intensity (SUHII) and the pixel-based Gaussian-simulated LSTs were predicted. The averaged MAE of our predicted SUHII across Chinese megacities is 0.67 K; and the MAE for the LST is generally less than 1.5 K. The incorporation of meteorological variables was shown to greatly contribute to the predicted daily SUHIIs. We consider our study, by achieving an attempt to the SUHI prediction, can improve the understanding of the SUHI mitigation.