Road network planning is fundamental for the forest areas appropriate to put into operation. And it is difficult to achieve the optimum goal in the total costs during the planning of road networks in particularly forest ecosystems through traditional methods, because variables of natural ecosystems (living and nonliving elements) have impacts at different degrees on road network plans. Fortunately, use of developed decision support systems (DSS) has capacity to gather and comparing with several decision variables, and that reveals impact degrees. In this study, multi-criteria evaluation (MCE) as DSS study were conducted in conversion of forests in coppice forests to high forests and reorganization of forest roads. Slope, aspect, road density, distance to road, land use and distance to mainstreams were used as criteria-decision variables to be used in forest road network planning. Determined degrees of decision variables were classified and clarified with fuzzy logic approach. The most cost-effective road routes were created along with calculated accumulative cost surface that is permeable layer for least-cost path analysis on this surface by combining the variables. Road network plan was created gradually by 3 different periods in coppice forest areas. Consequently, opening up rate with 3rd period road network plan by using GIS that was determined as 67.22% and road density was calculated as 17.07m/ha. After, performing expert-controlled corrections on road network considering land to increasing opening-up activities of production forest rate and achieving optimum road density goal, opening up rate and road density were calculated as 70.22% and 20.12 m/ha, respectively. As a result, expert-controlled corrections were necessary to correct the possible errors that arising from the precisions and upgrades of the data used because of data quality and site-specific in reality.