Recents studies have been demonstrated how useful and fundamental psychological aspects such as people Personality Traits and Emotions are during human decision-making process. Some research towards the identification and model of users Emotions have been done by Affective Computing researchers, however Personality Traits have been quite neglected. The World Wide Web is an enormous source of products and services available for people. There is a huge effort done by scientists towards the creation of effective strategies to personalize those products/services for each people interested in using them. By storing Personality Traits in User Profiles we intend to enable Recommender Systems in order to deduce more interesting recommendations for users acting pro-actively to offer them products/services as a consequence of a prediction of their future needs and behaviors. To fill this gap, in this work, we propose the interpretation, modeling, formalization, storing and application of Personality Traits in User Profile, followed by an experimentation developed in the context of Recommender Systems.