Magnetic gears offer several advantages over mechanical transmissions. However, across a broad range of research studies, their practical performance has not matched design predictions. Even with extensive 3D Finite Element Analysis (FEA), large discrepancies of 4% to 10% can existusually attributed to manufacturing error. Research studies typically assume ideal realization of the prototype geometry while employing basic, poorly characterized manufacturing processes in the hardware development. Geometric deviations due to manufacturing error are difficult to predict and inherently random. Therefore, their effect needs to be assessed through a statistical approach, which requires a rapid but accurate model of the gear. This paper assesses the effect of geometric error on the performance of a magnetic gear using a new computationally efficient asymmetric analytical model to conduct a Monte-Carlo simulation. The analytical technique is validated by comparing the results with a finite element solution and very close agreement is observed. By repeatedly analyzing the gear, with the position and size of each pole piece independently varied each time, a resultant distribution of performance can be derived. It is also shown that, for this case study, the distribution derived using the analytical model can be scaled to match the equivalent, but much more computationally onerous, FEA based solution. A predicted statistical distribution of a gear's performance, based on a set of manufacturing tolerances, would provide designers with a more realistic estimate of a gear's capability than an idealized analysis. This will be increasingly important as magnetic gears become more widely adopted.