Introduction: Markov models are employed in economic analyses to evaluate all possible expectations in a dilemna. The introduction of a new clinical protocol (basiliximab induction with calcineurin-sparing protocols) for a group of kidney transplant recipients receiving organs from marginal donors was validated with a Markov simulation model. Hypothesis: Calcineurin-sparing protocols using anti-IL-2/antibody induction (Simulect) show a beneficial effect on initial kidney function, reducing transplantation costs reception based upon mean length of stay, mean admission cost, and incidences of delayed graft function and complications during the first month after transplant. Patients and Methods: A Markov simulation model was established following three different chains. A calcineurin-free regimen with basiliximab induction (chain A), a calcineurin-sparing protocol with basiliximab induction (chain 13), and a conventional immunosuppressive regimen (chain C). After designing the Markov chain and cohorts, 31 patients from the "old to old" program were assigned to each chain eight to chain A, (eight to chain 13, and 15 to chain C). A month after transplantation a cost-benefit study was performed guided by the three branches of the Markov model. Results: The Markov model showed a benefit of induction therapies in elderly patients. A cost-benefit model showed that after a month there was a clear benefit from Calcineurin = free plus basiliximab induction therapies, with a slight benefit from calcineurin-sparing protocol. Conclusions: Markov models are extremely useful when introducing new clinical therapies. In our transplant program, a cost-effective analysis of outcomes in old patients using the Markov model showed a clear benefit of calcineurin-sparing protocols with basixilimab induction.