In software programs, most of the time, there is a chance for occurrence of faults in general, and exception faults in particular. Localizing those pieces of code that are responsible for a particular fault is one of the most complicated tasks, and it can produce incorrect results if done manually. Semi-automated and fully-automated techniques have been introduced to overcome this issue. However, despite recent advances in fault localization techniques, they are not necessarily applicable to Android applications because of their special characteristics such as context-awareness, use of sensors, being executable on various mobile devices, limited hardware resources, etc. To this aim, in this paper, a semi-automated hybrid method is introduced that combines static and dynamic analyses to localize exception faults in Android applications. Our evaluations of nine open source Android applications of di erent sizes with various exceptions show that the technique proposed in this paper can correctly identify root causes of the occurred exceptions. These results indicate that our proposed approach is e ective in practice in localizing exception faults in Android applications.