Implementing error-resilient business processing is a critical aspect of modern digitization initiatives, particularly when processes are automated using workflow engines. Automated business processes, modeled using Business Process Model and Notation (BPMN) or other modeling languages, must be designed to handle errors effectively to ensure reliability, maintainability, and robustness. Error situations can arise due to various reasons, such as system failures, data inconsistencies, external service disruptions, or business rule violations. The choice of an appropriate error-handling strategy depends on multiple factors, including the type of error, the operational context, and the required quality attributes such as availability, consistency, and fault tolerance. This paper presents eight distinct design patterns for handling errors in both analytical and executable business process modeling. These patterns provide structured approaches to error resolution, recovery, and mitigation, enabling organizations to build resilient workflows that minimize disruptions and ensure seamless execution. By applying these patterns, organizations can enhance their ability to recover from failures, maintain business continuity, and improve overall process reliability. The presented design patterns serve as a guideline for business analysts, process designers, and software engineers in developing robust business processes that are both adaptable and fault-tolerant. This work contributes to the field of business process management (BPM) by offering practical strategies that bridge the gap between theoretical process modeling and real-world execution challenges.