Focal cortical dysplasia (FCD) is one of the main causes of refractory epilepsy. There is no self-sufficient method in order to evidence the presence and location of FCD, making complete diagnosis very difficult. Although some studies have addressed FCD identification, image texture is poorly explored. This study evaluated pre and post-surgical magnetic resonance images (MRI) of epilepsy patients in order to test Machine Learning classifiers and their ability to identify dysplasia using texture features and cortical thickness. Precision and recall scores suggest the capabilities of the proposed methodology in responding to the presence of FCD tissue.