Estimating the deadline of a real-lime task is a necessary prerequisite to the applications that have strict timing constraints, such as real-time systems design. This paper shows how Monte-Carlo simulation can be used as a space-efficient way of analyzing Timed Petri nets to predict whether the system specified tan satisfy its real-time deadlines. For the purpose, Extended Timed Petri Net (XTPN), an extension of conventional Timed Petri net. and its execution rule, using Monte-Carlo technique, are newly defined. A simple simulation scheme with less memory space is presented as a way of estimating the deadline of a real-time task modeled in XTPN. And the comparison between the analytical and simulation results is given, The problem addressed here is to find the probabilities of meeting given deadlines.