Suicide is an internationally recognized burden of health, but little progress has been made towards creating effective risk assessment tools. In order to be used in clinical settings, these tools must prospectively differentiate between future attempters and nonattempters; do so with adequate sensitivity and specificity; and do so in a clinically useful time frame. Given these criteria, we review the state of classic suicide risk assessment tools, which rely on self-report of suicidal symptoms or clinical risk factors (i.e., hopelessness). In summary, there are substantial limitations to such paper-based tools given the incentives to deny suicidal thoughts, a lack of replication and the lengthy follow-up time frames identified by most studies. Next, we review the evidence for a new type of computer-based risk assessment tool that utilizes implicit cognitive associations with suicide as an indicator of implicit biases. By comparing the classic self-report versus cognitive risk assessment techniques, substantial advantages have emerged regarding predictive validity when using this cognitive test approach. Although these tools may take additional efforts to integrate into clinical assessments, they offer substantial advantages through their ability to predict short-term (~6 month) suicidal behavior. It is not suggested that such tools replace the utility and importance of clinical interviews or expertise, but that they could rather provide a valid tool to inform clinician decisions for acute care.