The main purpose of our research is developing a mathematic model which will select cargo fleet. The select criteria are specific production quantity. Basic variable is lifecycle of a truck. We have analyzed the market of new and used trucks and determined dependency between truck price, production and service life. Price change dynamics has been determined. After that, we've revealed dependency between the truck's annual haulage and its lifecycle. Based on this data, a new coefficient was introduced. It shows the extent to which the truck loses productivity. In order to show the dynamics of coefficient change, a function was approximated. A mathematic model was built upon this function. This model should select the optimal truck in terms of its lifecycle. Another model was built for the corresponding self-cost. It uses tariff change data that depends on the length of a trip. At the same time, it uses self-cost data that depends on lifecycle of a truck. Generally, these models should optimize car fleet in terms of lifecycle and productivity of trucks. Truck fleet must comply with production goals and be less expensive.