Establishing federal budgets for cloud infrastructure costs prior to selecting a cloud provider requires vendor agnostic cost estimating methods. These methods need to reflect the correlation between rates for a variety of infrastructure instances across all viable cloud service providers. This paper describes research and validation leading to CERs and models based on 28,000 virtual machine and storage instances. The predictive analytic approaches presented in this paper can provide valid and verifiable vendor agnostic estimates. This research was also submitted to the ICEAA 2020 conference but the data and methodology will be updated.