Fish year-class strength (YCS) has been estimated via longitudinal analysis of catch-at-age data and via catch-curve regression, but no study has compared the two approaches. The objective of this study was to compare YCS estimates derived from both approaches applied to catch-at-age data for the lake trout (Salvelinus namaycush) population in the main basin of Lake Huron, one of the Laurentian Great Lakes of North America. YCS was reconstructed for both hatchery-stocked and wild lake trout. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to compare 14 linear mixed-effects models for longitudinal analysis of catch-at-age data, and three linear mixed-effects models for catch-curve regression. From the best models based on AIC or BIC comparisons, YCS estimates with year-class as a fixed effect were consistent with those estimated with year-class as a random effect. Patterns and trends in the YCS estimates were also the same or similar between the longitudinal analysis of catch-at-age data approach and the catch-curve regression approach, suggesting that both modeling approaches are applicable to a variety of fish populations. indicating that both approaches provide robust measures of YCS. Potential bias in using the approach of catch-curve regression could be caused by abrupt changes in adult mortality. It is also critical to recognize multiple recruitment origins for using the approach of longitudinal analysis of catch-at-age data.