Robotic Process Automation (RPA) is an emerging technology that enables the automation of well-defined and repetitive back office processes by providing a virtual workforce. Even though RPA draws much corporate attention in recent years, many RPA projects fail or lack behind expectations. A major reason is the automation of wrong processes, mainly driven by a lack of structured processes and objective methods to identify and select suitable process candidates. Therefore, the goal of this paper is to develop a generalizable method to detect, prioritize, and select process candidates for the automation with RPA. The paper follows the principles of Design Science Research and includes a literature review, expert interviews, and an extensive survey based on the Analytic Hierarchy Process approach with RPA developers, consultants, and end users. As a result, we present a three-step approach and a quantifiable model to objectively prioritize and select suitable RPA process candidates based on suitability values. We empirically show that the most important criteria to select suitable RPA process candidates are a high degree of standardization and high volumes.