Hard real-time tasks are associated with strict deadlines. Classical scheduling heuristics ensure fairness among tasks and prevent deadlock, but are not concerned with deadline compliance. Hence, there is a need for scheduling heuristics which prioritize tasks in a real-time system in a manner which guarantees timely completion of maximum number of tasks. In this paper, several static heuristics for mapping hard real-time tasks to machines in a heterogeneous distributed system have been described. These heuristics differ in their method of prioritizing tasks for scheduling, which results in varied performance. The heuristics have been outlined and simulated using a common set of assumptions. The performance parameter considered in this study is the number of user satisfied tasks.