Effective loop-scheduling can significantly reduce the total execution time of a program on grid environments, especially for loop-intensive applications. This paper describes a two-phased method, named HPLS (Hybrid Parallel Loop Scheduling), to dynamically schedule loop iterations of a program on grid environments. In the first phase, most of the workload is dispatched to each node for execution according to its performance. Then, some well-known self-scheduling scheme is utilized to schedule the remaining workload. Experimental results showed that in most cases our approach could produce more efficient scheduling than previous schemes on our testbed grid. In addition, the results suggest that our approach is suitable for loop scheduling on grid environments.