The World Wide Web is a great source of products and services available to people. Scientists have made a huge effort to create effective strategies to personalize those products/services for anyone willing to use them. The personalization may be provided by Recommender Systems which are able to match people’s preferences to specific products or services. Scientists from different research areas such as Psychology, Neurology and Affective Computing agree that human reasoning and decision-making are hardly ever affected by psychological aspects. Thus, to maintain the same level of personalized service provided by humans, computers should also reason, taking into account users’ psychological aspects. Nevertheless, the psychological aspects have, unfortunately, not been highly applied in Recommender Systems during their decision-making process. In this work we discuss the evidences that the use of Personality Traits in Recommender Systems might be coherent and effective for the improvement of the recommendations for users and, therefore, act proactively towards users’ needs, offering more adaptable products and services according to their future needs.