The scientists in Korea created models to predict when frost will occur in the spring using statistical techniques. They compared two methods, logistic regression and decision trees, to see which was more accurate. The decision tree model was found to be better for giving timely warnings about frost. By using fewer variables, the decision tree model was able to predict frost occurrences with high accuracy. This research suggests that improving these models to include local features could make them even more effective in preventing damage to crops from frost.