Suicide is a major health issue with considerable human and economic costs. There have been many attempts to develop techniques capable of predicting future suicidal behavior, but known risk factors are insufficiently specific. However, during the last decades, technical developments have made possible the use of new technologies to assess potential clinical markers for psychiatric patients. In many cases the technologies are affordable, wearable and interconnected, multiplying the wealth of data resulting from their use. Quite logically, psychiatrists from all over the world are investing in recently developed devices for their research projects and have consequently started to collaborate with engineering and pattern recognition groups in the study of potential clinical markers. These groups provide the expertise and computational methods required to process this wealth of data, and can improve the classification accuracy to predict a certain condition using data mining techniques. In the field of suicidal behavior, new devices that capture promising predictors such as electrodermal response activity, some facial expressions or speech properties have been developed and are being tested. In view of these facts, during the workshop we will review some of the new methodologies that can be used for the assessment of suicidal risk and how can multidisciplinary and complementary approaches be implemented.