Personality disorders are characterized by persistent deviations in inner experience and behavior that do not align with societal norms, according to the American Psychiatric Association (2013). These conditions significantly affect the quality of life and give rise to problems in emotion regulation, strong impulsivity, identity disturbances, and other severe symptoms. The aim of this chapter is to present recent advancements in the understanding of the neural bases of personality pathology and the possibility to extract neuropredictive models of such disorders. To begin with, the reader will be introduced to some of the available machine learning methods used inside the field of personality neuroscience. Then specific personality pathologies will be presented: borderline, narcissistic, and antisocial in the form of a dark triad of personality. Finally, trait anxiety defined as a stable personality condition will be discussed. By integrating findings from neuroimaging methods and artificial intelligence techniques, this chapter aims to highlight the potential of neuropredictive models to revolutionize the diagnosis, treatment, and theoretical conceptualization of personality disorders.