Live migration of a virtual machine (VM) is a powerful technique with benefits of server maintenance, resource management, dynamic workload re-balance, etc. Modern research has effectively reduced the VM live migration (VMLM) time to dozens of milliseconds, but live migration still exhibits failures if it cannot terminate within the given time constraint. The ability to predict this type of failure can avoid wasting networking and computing resources on the VM migration, and the associated system performance degradation caused by wasting these resources. The cost of VM live migration is highly dependent on the application workload of the VM, which may undergo frequent changes. At the same time, the available system resources for VM migration can also change substantially and frequently. To account for these issues, we present a solution called MigVisor, which can accurately predict the behaviour of VM migration using working-set model. This can enable system managers to predict the migration cost and enhance the system management efficacy. The experimental results prove the design suitability and show that the MigVisor has a high prediction accuracy since the average relative error between the predicted value and the measured value is only 6.2%$\sim$9%.