This journal article introduces the Z'-factor, a commonly used simple statistical method to evaluate the quality of High-Throughput Screening (HTS) and High-Content Screening (HCS) assays. The Z'-factor is a dimensionless parameter that reflects both the assay signal dynamic range and the data variation associated with signal measurements, making it suitable for assay quality assessment. Developed by Zhang, Chung, and Oldenburg, the Z'-factor is a critical tool for comparing and evaluating the quality of assays, and it is widely utilized in assay optimization and validation. An ideal assay has a Z' value close to 1, indicating a large dynamic range and small data variability, while values close to zero or negative suggest that assay conditions may not be optimized or the assay format is not feasible. Unlike the Z-factor, which evaluates the quality of a configured assay including the effect of a compound library, the Z'-factor specifically assesses the quality of the assay itself, independent of test compounds, by using only control data. This makes it particularly useful during the developmental phase of an assay before the experimental phase. This publication is fundamental for researchers in drug discovery and biomolecular screening, providing a robust statistical metric for ensuring the reliability and quality of high-throughput experiments.