This work presents an emotion prediction method-ology based on face, galvanic skin response and heart rate applied on flight simulator context. This important contribution regarding the emotional events along simulated flights considered eight beginner users of flight simulator (n=8). These flights were executed according to the basic concepts of visual flight rules (VFR). The acquired physiological sensing were: heart rate (HR) and galvanic skin response (GSR). One small camera and the Face Reader software were also used to record the users’ face to acquire on off-line processing of the facial emotions during these flights. The considered emotions were: happy, sad, angry, surprised, scared and disgust. To predict these emotions, the Artificial Neural Network (ANN) was applied. The experiment shows that is possible to predict emotions using this data and the best predict model was reached with 2 hidden layers, having a minimum squared error of 0.219.