Friend recommendation system (FRS) is an essential part of any social network system. With the popularity of social network sites, many FRSs have been proposed in the past few years. However, most of them are homophily based systems. In other words, these systems recommend people that share common features. Homophily based FRS is accurate when the common feature is a physical or social feature, such as age, race, location, job, or lifestyle. However, this is not necessarily the case with personality types. Having a given personality type does not necessarily mean that a person is compatible with people having the same personality type. Therefore, this paper presents and evaluates an FRS based on the Big-Five personality traits model and hybrid filtering, in which the friend recommendation process is based on personality traits and users’ harmony rating. To validate the proposed system’s accuracy, a personality-based social network site named PersoNet is implemented. User rating results show that PersoNet performs better than a collaborative filtering (CF)-based FRS in terms of precision and recall.