Abstract : Probabilistic analysis are considered nowadays an interesting solution for real-time systems as the probability
of appearance of worst-case values is small (10−45 per hour of functioning) compared to the accepted
probability of failure (10−9 per hour of functioning for the highest safety level in avionics). In order to take
into account this information, Burns and Edgar  have introduced the notion of probabilistic worst case
execution time (pWCET). The pWCET of a program is bounding the probability that the execution time
of that program exceeds a given value. A possible method to estimate the pWCET is based on measurements
and the associated analysis is called measurement-based probabilistic timing analysis (MBPTA). Such
method has been proposed by Cucu-Grosjean et al.  and the obtained estimate is sensitive to the observed
execution times. To our best knowledge this dependence of MBPTA on the observations is an open problem.
Within this paper we propose a first solution based on a mixed model using genetic algorithms.