The popular General/Property-Casualty Insurance chain ladder method was first expanded to include variance calculations by Mack. Our presentation will expand the chain ladder method’s stochastic functionality. The purpose of this presentation is to introduce more statistical rigor and help bridge the gap between practice and statistical theory. We will expand the regression approach of Murphy so that selected link ratios other than simple or volume weighted averages can be seen as optimizing a rigorous statistical model. We will discuss formulas for the parameter risk and process risk of ultimate losses projected from such selected link ratios. We will discuss residual analysis and statistical measures for validating the selected factors. Using data previously analyzed in the literature, we will compare stochastic results from the popular application of the Mack formula to those based on our model. It is hoped that this presentation will provide the actuarial practitioner with a statistically rigorous framework with which to measure objectively the appropriateness of the chain ladder deterministic and stochastic results, make more informed judgmental selections, and avoid injudicious conclusions based on potentially inappropriate assumptions. A number of real-life examples will be also discussed and the results of popular stochastic projection methods will be compared based on different selected development factor assumptions.