With the rapid development of high-speed wide-area networks and powerful yet low-cost computational resources, grid computing has emerged as an attractive computing paradigm. It provides resources for solving large scientific applications. It is typically composed of heterogeneous resources such as clusters or sites at different administrative domains connected by networks with widely varying performance characteristics. The service level of the grid software infrastructure provides two essential functions for workload and resource management. To efficiently utilize the resources at these environments, effective load balancing and resource management policies are fundamentally important. This paper addresses the problem of load balancing and task migration in grid computing environments. We propose a fully decentralized two-level load balancing policy for computationally intensive tasks on a heterogeneous multi-cluster grid environment. It resolves the single point of failure problem which many of the current policies suffer from. In this policy, any site manager receives two kinds of tasks namely, remote tasks arriving from its associated local grid manager, and local tasks submitted directly to the site manager by local users in its domain, which makes this policy closer to reality and distinguishes it from any other similar policy. It distributes the grid workload based on the resources occupation ratio and the communication cost. The grid overall mean task response time is considered as the main performance metric that need to be minimized. The simulation results show that the proposed load balancing policy improves the grid overall mean task response time.