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Demand for data-limited stock assessment methods is increasing, and new methods are being developed rapidly. One class of these methods requires only catch time series and, in some cases, information about life history or fishery characteristics, to estimate stock status. These catch-only methods (COMs) range from statistical models trained on data-rich stocks to mechanistic population models that make assumptions about changes in fishing effort. We review 11 COMs, comparing performance through application to data-rich stocks and simulated fisheries. The catch-only methods evaluated here produce imprecise and biased estimates of B/B_MSY, especially for stocks that are lightly exploited. They were also generally poor classifiers of stock status. While no method performed best across all stocks, ensembles of multiple COMs generally performed better than individual COMs. We advocate for testing new …