This paper presents the analyses of a methodology to capture quantitative reliability from multi element integrated systems of processing environments of the International Space Station (ISS) Program at the Kennedy Space Center (KSC) in Florida. The analysis uses the combination of Baker's Generic Classification Scheme, Goodness of Fit and the Laplace techniques to classify the multi-element integrated systems within processes into single (human, hardware, software), dual (hardware-software, software-human, humanhardware), and multi elements (hardware-software-human) interactions. The technique provides practitioners with immediate statistical significance of reliability growth or deterioration in a process. The significance of research lies within the inclusion of first order element interactions of dual and multi elements to properly estimate standard reliability. Qualitative and quantitative decisions are made to understand mechanisms across simulated and operationally configured tests (at the system, subsystem, element, element interaction, and element attributes levels) as well as scrutinize certain problems within steps of various sequenced processes. The analyses mark the first time a logically statistical technique is utilized in an integrated approach to assess total system reliability of simultaneous failures in real field performance. The overall reliability assessment reflects process success rate over the development test time.