OBJECTIVES: Remaining life expectancy (RLE) and quality-adjusted life expectancy (QALE) are standard outcomes of decision-analytic Markov models, but their evaluation in decision trees is less straightforward. We compared Gompertz approximation (GPA) and Declining Exponential Approximation of Life Expectancy (DEALE), using life table method as gold standard. METHODS: All analyses were performed for additive and multiplicative models for disease-specific mortality rates (DSM). Background mortality was estimated from statistical life table data. In our base case analysis, we set the mortality rate difference in the additive model being twice the background mortality at age 45. We set the relative mortality rate ratio to three in the multiplicative model. We used 1) the formulas by Pollard based on the Gompertz function, and 2) the DEALE formulas to calculate undiscounted and discounted RLE and QALE (3% annual discount rate). Results were compared to actuarial life table analysis. Bias was defined as percent deviation from the sum of RLE for ages 30-89. DSM and discount rates were varied in one-way sensitivity analysis. RESULTS: Both approximation methods underestimated undiscounted RLE for both, the additive and multiplicative model. Base case results for men: for the multiplicative model, GPA (bias -4%) performed better than DEALE (-49%), whereas for the additive model, DEALE (-6%) was superior to GPA (-25%). Results for women showed similar patterns regarding magnitude and direction of bias. The use of time-independent disease-specific utility decrements yielded similar patterns for QALE. When varying DSM in sensitivity analysis, bias was positively correlated with DSM, but bias direction (sign) and ranking of both methods did not change. Similarly, changing discount rates did not alter the bias pattern. CONCLUSIONS: Based on our simulations, the Gompertz function should be preferred for multiplicative models and the DEALE approach for additive models. The magnitude of the bias depends strongly on model parameters.