This paper by J.M. Hoenig explores the empirical use of longevity data to estimate mortality rates in fish, cetaceans, and mollusks. The author develops a general regression equation to predict total mortality rates from maximum ages, building on previous studies that used life history parameters to predict difficult-to-estimate values. The relationship between mortality rate and maximum age is explored, and the paper presents a model where the mortality rate is assumed to be constant after early life stages. The model is linearized by plotting the mortality rate against the reciprocal of maximum age or the logarithm of the mortality rate against the logarithm of maximum age. The results show a strong linear relationship between these variables, suggesting that the regression equation can be used for predictive purposes across all three groups. The paper discusses the limitations of the technique, such as the lack of consideration for sample size and the assumption of constant mortality rate, and highlights its applications in various scenarios, including preliminary estimates, limited data sets, and cases with variable recruitment. The regression technique is found to have significant predictive power but requires further sophisticated statistical methods to address its limitations.This paper by J.M. Hoenig explores the empirical use of longevity data to estimate mortality rates in fish, cetaceans, and mollusks. The author develops a general regression equation to predict total mortality rates from maximum ages, building on previous studies that used life history parameters to predict difficult-to-estimate values. The relationship between mortality rate and maximum age is explored, and the paper presents a model where the mortality rate is assumed to be constant after early life stages. The model is linearized by plotting the mortality rate against the reciprocal of maximum age or the logarithm of the mortality rate against the logarithm of maximum age. The results show a strong linear relationship between these variables, suggesting that the regression equation can be used for predictive purposes across all three groups. The paper discusses the limitations of the technique, such as the lack of consideration for sample size and the assumption of constant mortality rate, and highlights its applications in various scenarios, including preliminary estimates, limited data sets, and cases with variable recruitment. The regression technique is found to have significant predictive power but requires further sophisticated statistical methods to address its limitations.