Abstract: First-Frost disaster is a key factor of affecting the outcome of the kharif crop in Suzhou city. This paper, according to the mechanism of seasonal event grey prediction and multi-model discrete cover, establishes different zero-start-point catastrophic subsequences and multi-GM(1,1) models and by optimizing the choice of model by grey correlation degree and by means of successive modeling of innovation and gray data, conducts a dynamic prediction of grey target interval of the First-Frost period, thus to ascertain the most possible year of disaster by whitening multi-model discrete cover according to frequency of disaster happening, which is conducive to long-term prediction of the First-Frost period after experiments with significant effects.