Typically organizations implement simulation by focusing on an initial application or two. At this stage the confidence and appropriate use of the results are easily communicated using informal methods. However, as simulation adoption spreads through an organization and is applied to an increasing range of applications it becomes important to formally assess and communicate the maturity of the simulation methodology and appropriate uses for the results. This helps address several issues. First, not all simulations need to be performed at the highest level of rigor, early in a project simplified analyses may be appropriate to sort concepts or justify further effort. Second, not all simulations are validated to the same level, some may be thoroughly validated and may be accepted in lieu of testing, while others may represent an initial effort at simulation with little or no validation completed. Third, often prior simulations become the starting point for additional work conducted at a later date, perhaps by a different analyst who may not be aware of the maturity level of the prior work. Fourth, requestors and customers of simulation often lack the familiarity and knowledge to judge the level of simulation maturity or what level of confidence they should place in the results. Adoption of a formal system for assessing and stating simulation maturity provides a means to clearly define and communicate the confidence in the analysis. This work is an expansion of a brief presentation on the topic given by the author at the NRC22 conference. Included is a review of some of the existing methods used for simulation maturity assessment. Also discussed will be the competing needs that a maturity assessment needs to satisfy. Typically the recipient of the analysis report needs a simple, concise statement of the simulation maturity and how the results may be properly used. On the other hand, simulation analysts need a more detailed assessment that helps them consider multiple aspects of simulation maturity, including geometric fidelity, simplifying assumptions, selected representations of physics and materials, mesh adequacy, level of verification, extent of validation, etc. This helps facilitate a consistent assessment of maturity when simulation is spread across a group or between multiple locations, and also provides a clear evaluation of what aspects of the simulation need to be improved if the resulting confidence level is not adequate for the requestor’s needs. A hybrid system which uses an internally facing detailed assessment for use by simulation experts coupled with an outward facing single numerical score of simulation maturity for the analysis recipients will be presented.