Examination timetabling is a well-studied combinatorial optimization problem. We present a new hybrid algorithm for examination timetabling, consisting of three phases: a constraint programming phase to develop an initial solution, a simulated annealing phase to improve the quality of solution, and a hill climbing phase for further improvement. The examination timetabling problem at the University of Melbourne is introduced, and the hybrid method is proved to be superior to the current method employed by the University. Finally, the hybrid method is compared to established methods on the publicly available data sets, and found to perform well in comparison.