In this study, properties of software development cost were analyzed by applying the Weibull family lifetime distributions (Lindley, Rayleigh, Type-2 Gumbel) which are utilized in the reliability evaluation field to the software development model. Also, the Weibull family distribution models were compared with the Goel-Okumoto basic model to verify cost property, and the optimal development cost model was presented. For this study, a total solution was performed using software failure time data generated during desktop application operation, parameter calculations were solved using the maximum likelihood estimation (MLE) method, and nonlinear equations were calculated using the binary method. As a result, first, when the testing cost per unit time and the cost of eliminating a single fault detected during the development testing process increase, the development cost increases, but the release time does not change. However, if the fault correction cost detected by the operator during normal system operation increases, the development cost increased along with the delay of the release time. Second, it can be confirmed that the Lindley distribution model is efficient among the proposed models as it has the best performance in terms of development cost and releasing time. Third, if software developers and operators can use this analytical information efficiently, they can explore the cost of economic development by predicting relevant attributes.