Process mining, introduced by Aalst in 2004, is a data analytics technology designed to extract process-related information from historical event logs. This field has seen significant growth, offering numerous tools and applications that provide data-driven solutions and support for process improvements. Modern business processes, including management, modeling, and analysis, are primarily conducted through process-aware information systems such as Customer Relationship Systems, Accounting and Finance Management Systems, and Enterprise Resource Systems, which collect process events in various event logs. Visualization of process mining can be very valuable to the decision-making process. Visual representations of mined process data allow participants of all sides to easily interpret complex information, identify patterns, and detect anomalies. By transforming abstract data into intuitive visual formats, decision-making team can gain genuinely worth insights faster and more accurate. This facilitates better understanding of process performance, helps detect inefficiencies, and supports the optimization of business activities. Effective visualizations also enhance communication among team members and other part participants, ensuring that data-driven decisions are well-informed and aligned with organizational goals. Thus, process mining visualization is a crucial tool for leveraging data to drive strategic and operational improvements. The main purpose of the paper is to present several process mining visualization examples resulting from the analysis of historical event logs.