1. Semi-Markov models explicitly define the distribution of waiting time duration and have been used as a convenient framework for modelling the time spent in one physiological state in previous biological studies. 2. Here, we focus on the modelling of the time spent within a life-cycle stage (e.g. juvenile, adult and old) by individuals over their lifetime from Capture-Mark-Recapture data, which are commonly used to estimate demographic parameters in free-ranging populations. 3. We propose a parametric model (1) with a semi-Markov state, (2) associated to a hazard function and (3) accounting for imperfect detection to assess reliably survival patterns from birth to death. 4. These models indeed outperform models with a linear trend or a quadratic form, often selected as the best model for survival in capture-recapture studies. 5. Moreover, our approach offers the first opportunity to estimate statistically rather than visually the age of the onset of actuarial senescence, associated with confidence intervals. 6. The application of this new approach to the detailed long-term study of survival in roe deer at Trois Fontaines (France) illustrates the relevance of semi-Markov models to assess survival patterns from birth to death.