Nowadays, reliability analysis has become an integral part of system design and operating. This is especially true for systems performing critical tasks. Moreover, recent works in reliability involving the use of probabilistic graphical models, also known as bayesian networks, have been proved relevant. This paper aims to describe a general methodology to model the stochastic degradation process of a complex system, allowing any kind of state sojourn distributions along with an accurate context description. We meet these objectives using a specific dynamic graphical model, namely a graphical duration model. In this article, we give qualitative and quantitative descriptions of the proposed model and describe a simple algorithm to estimate the system reliability and some of its related metrics. Finally, we illustrate this approach by applying our methodology to a three-states system subjected to one context variable and with non exponential duration distributions.