This study investigates the classification of developing and nondeveloping tropical disturbances in the western North Pacific (WNP) through the C4.5 algorithm. A decision tree is built based on this algorithm and can be used as a tool to predict future tropical cyclone (TC) genesis events. The results show that the maximum 800-hPa relative vorticity, SST, precipitation rate, divergence averaged between 1000-and 500-hPa levels, and 300-hPa air temperature anomaly are the five most important variables for separating the developing and nondeveloping tropical disturbances. This algorithm also unravels the thresholds of the five variables (i.e., 4.2 3 10 25 s 21 for maximum 800-hPa relative vorticity, 28.28C for SST, 0.1 mm h 21 for precipitation rate, 20.7 3 10 26 s 21 for vertically averaged convergence, and 0.58C for 300-hPa air temperature anomaly). Six rules are derived from the decision tree. The classification accuracy of this decision tree is 81.7% for the 2004-10 cases. The hindcast accuracy for the 2011-13 dataset is 84.6%.