In recent years, the improvement of cloud computing and mobile computing techniques has led to a variety of mobile applications in the app store. For instance, the garbage truck app is required to provide the immediate location of garbage truck, the location of collection point, and forecasted arrival time for mobile user. Therefore, this study designs and develops a garbage truck fleet management system (GTFMS) with a an arrival time prediction method based on cloud computing techniques. GTFMS is a three-component system including on-board units on garbage trucks, a fleet management system, and a garbage truck app. Furthermore, an arrival time prediction method based on multiple-regression models and cloud computing technique is designed and implemented in the fleet management system, and the garbage truck app can retrieve the predicted arrival time via web services. In experiments, the results showed that the mean accuracy of predicted arrival time by the proposed method is about 81.45%. Consequently, the GTFMS can provide the precise forecasted arrival time for mobile user.