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An efficient airport pavement management system is essential to judge current runway conditions and predict future runway conditions and support decisions. However, one of the limitations is insufficient scope for analysis of the infrastructure environment, particularly regarding loss of revenue due to the need for total or partial closure of the runway in life-cycle cost analysis (LCCA) approaches. In this article, a method is presented for calculating indirect/user costs based on the net present value related to closed runway time in the cash flow variable. This method integrates passenger demand forecasts based on machine learning and the net operating revenue of an airport. Relying on a case study of Brasília International Airport, the consideration of a variable called the ‘equivalent operational susceptibility area’ improved understanding of the financial impacts on indirect/user costs and direct/owner costs. This variable enabled visualisation of the conditions for the financial feasibility of pavement intervention scenarios. The proposed method uses the required time of runway closure and the area to be maintained as balance weights between the direct and indirect costs of LCCA. Therefore, it is not reasonable to relegate indirect/user costs to estimated values or aircraft and passenger movement fees.