Receiver operating characteristic (ROC) analysis is the standard tool for studying recognition memory. In particular, the curvilinearity and the y-offset of recognition ROC curves have been interpreted as indicative of either memory strength (single-process models) or different memory processes (dual-process model). The distinction between familiarity and recollection has been widely studied in cognitive neuroscience in a variety of conditions, including lesions of different brain regions. We develop a computational model that explicitly shows how performance in recognition memory is affected by a complex and, as yet, underappreciated interplay of various factors, such as stimulus statistics, memory processing, and decision-making. We demonstrate that (1) the factors in the model affect recognition ROC curves in unexpected ways, (2) fitting R and F parameters according to the dual-process model is not particularly useful for understanding the underlying processes, and (3) the variability of recognition ROC curves and the controversies they have caused might be due to the uncontrolled variability in the contributing factors. Although our model is abstract, its functional components can be mapped onto brain regions, which are involved in corresponding functions. This enables us to reproduce and interpret in a coherent framework the diverse effects on recognition memory that have been reported in patients with frontal and hippocampal lesions. To conclude, our work highlights the importance of the rich interplay of a variety of factors in driving recognition memory performance, which has to be taken into account when interpreting recognition ROC curves.