Condition and cloud based prognostics offers the opportunities to reduce loss due to machine failures and delay in planning for maintenance activities and spare parts. The time complexity of the prognostics algorithms used for predicting imminent component failures or the remaining useful life of critical components plays a vital role in determining the accuracy and feasibility of prognostics systems. We discuss the infrastructure needs of cloud based prognostics and compare time complexity of different prognostics methods used to predict machine failures.