Considering damage to man-made structures by natural hazards in Turkey, landslides are the second most important hazard after earthquakes. For this reason, a large-scale study titled Turkish Landslide Inventory Project, has been carried out since 1998. During this project, some special, susceptibility, hazard and risk assessments have been performed. In this study, a landslide susceptibility map of a part of tectonic Kelkit Valley in the north of central Turkey was produced, employing binary logistic regression analyses. To achieve the most appropriate results some sensitivity analyses were also carried out. For this purpose, four different data sets were constructed considering conditioning factors used and sampling strategies applied for the training data sets in this study. As a consequence of the analyses, the most proper outcomes were obtained by using the data set in which continuous topographical parameters and lithological dummy variables were implemented together and 50% of training data set was taken from seed cells at random. Correct classification percentage and Root Mean Square Error (RMSE) values for the validation data for that case were estimated as 84.16% and 0.36, respectively. This prediction capability shows that the landslide susceptibility map produced in this research paper can be used for the planning of protective and mitigation measures in the region.