Many large computational problems depend on solutions to systems of linear equations. One widely used method of solving systems of linear equations is the Conjugate Gradient method (CG). Terminating CG after only a few iterations can save computational resources but can also cause an error in the solution to the system of linear equations, and this error can affect the larger problem. We examine how this error affects the larger problem using probabilistic numerics.