Distribution processes account for a large stake of direct costs in Large-Scale Retail Trade (LSRT) companies and here, more than in other industries, the quest for efficiency is critical to defend the low operating margins. Because here distribution networks endlessly vary, following the continuous opening and closing of stores, the company management needs synthetical metrics to estimate the transportation cost resulting from a hypothetic distribution configuration. The two data types that are always available to the logistic manager in a LSRT company are the stores’ addresses and their expected turnover. The aim of this paper is proposing a methodology for a synthetic estimation of the distribution cost related to a given distribution network, only leveraging on these data. This would allow LSTR companies to easily evaluate the impact of distribution decisions on transportation cost without recurring to complex and often impracticable simulative approaches. The methodology exploits a set of functions relating store locations, turnovers, distribution routes, mileages, fares and transportation costs. These functions have been calibrated upon the case of a LSRT company operating in south-east Italy and, subsequently, validated onto the case study of a different company in north Italy. The methodology has demonstrated to be satisfactorily generic to yield correct results also on very dissimilar industrial cases, showing the potentiality to support decision-making in distribution management for LSRT companies.