In the light of fast pace smart phone development, increasing numbers of applications are being developed to cater for portability. A real-time facial expression recognition application is develop that was tested in Windows Mobile environment. The underlying algorithm adopted in this work uses Boosting Naïve Bayesian (BNB) approach for recognition. We examine the structure of training data and the effect of attributes on the class probabilities through the use of Naïve Bayesian classifier (NBC). The experiments carried out show that we have achieved the important features of mobile application: speed and efficiency. This work is believed to be the first recorded initiative that de-ploys facial expression recognition into a mobile phone. It seeks to provide a launching point for a sound and portable mobile application that is capable of recognizing different facial expressions.