The adoption of technology for enhancing efficiency has become a widespread practice among companies. In recent years, the digital transformation movement has played a pivotal role in this effort, making substantial contributions. One of the fundamental pillars of digital transformation is digitalization, a strategy whose goal is to automate analog and manual activities. In this context, a widely adopted solution is known as Robotic Process Automation (RPA), which refers to software robots automating repetitive tasks to increase efficiency and reduce costs. However, a very difficult task is prioritizing because multiple variables must be considered. Inevitably, poor choices can lead to stress and inefficiency. In this article, a strategy is presented to overcome this issue: first employing Multi-Criteria Decision Making (MCDM), a methodology used to evaluate and prioritize alternatives in the presence of multiple criteria. Secondly, by Process Mining (PM), which involves analyzing event data recorded during business processes to gain insights into performance, compliance, and efficiency. Therefore, this approach involves the use of MCDM techniques for prioritization, combined with process mining to identify and assess the feasibility of automation with RPA, the application of which will be demonstrated in a case study. The findings provide valuable guidance for process practitioners seeking to leverage advanced technologies for process optimization.