Virtual machine (VM) consolidation is necessary for increasing the server utilization; however, it also leads to VM performance degradation. This work presents a method to predict the consolidated VMs performance from the critical system events data. Experiments are designed to demonstrate the effect of system events like interrupts, page faults, mutex operations, and context switching on the consolidated VMs. Results show that the host server counters are not reliable for such predictions. On the other hand, the coupling of the task execution time with the VM system events is an effective way to predict the consolidation performance. Results further show that the VM memory allocation plays an important part in the consolidated tasks performance. The system event data is also used to train an Artificial Neural Network (ANN) for performance prediction on three hypervisors; ESXi, Xen, and XenServer and similar results are observed in all three.