One way of obtaining information about reliability of units is to accelerate their life by testing at higher levels of stress (such as increasing elevated temperatures or voltages). Predicting the lifetime of a unit at normal operating conditions based on data collected at accelerated conditions is a common objective of these tests. Different models of accelerated life testing are used for such extrapolations. Two statistical based models are widely used: parametric models which require a prior specified lifetime distribution, and nonparametric models that relax of the assumption of the life time distribution. The proportional odds model is a nonparametric model in accelerated life testing based on the odds function and show that it gives a more accurate reliability estimates than proportional hazard model. This paper will concentrate on the models of proportional odds nonparametric accelerated life test for reliability prediction.