Scheduling computational tasks on processors is a key issue for high-performance computing. Although a large number of scheduling heuristics have been presented in the literature, most of them target only homogeneous resources. We present a new scheduling heuristic for heterogeneous processors, which improves the load-balancing achieved at each decision step while keeping a low complexity. Experimental comparisons with five heuristics taken from the literature (BIL, GDL, CPOP, HEFT and PCT) and using six classical testbeds, show very favomble results.