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This article is the second of a series of two articles. In the first article of the series, a new K v distribution model and an experimental methodology to measure the K v distribution were introduced. In this second part, the K v distribution is integrated into a lyo-simulation tool, to more accurately predict the variability of the product temperature, primary drying time, total sublimation mass flow and Pirani signal. The K v distribution is also integrated into the graphical design space. The impact of incorporating the R p distribution is briefly discussed. The comparison of the simulation tool with actual product temperature monitoring, Pirani signal or overall sublimation flow shows very good agreement in the case studies presented. Overall, the lyo-simulation incorporating the K v distribution is a very useful tool to support industrial development, i.e. process optimization, scale assessment, technology transfer, and troubleshooting of the lyophilization process., Competing Interests: Declaration of Competing Interests The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: All the authors worked for Sanofi at the time where the research work was done, except one working for Astek - IT&M STATS (contracting company for Sanofi). All the work was Sanofi financed., (Copyright © 2024. Published by Elsevier Inc.)