Wild boars belong to the most wide spread ungulates in the world. They are characterized by a well performed adaption to their environment mainly due to their omnivorous dietary. The wild boar population in Germany increased during the past three decades. Nowadays their high density leads to problems in agricultural areas due to damage of crops and plays a significant role as disease vector as the classical swine fever. For an effective population management population size information is of crucial importance. Different traditional methods exist to estimate population sizes as direct sightnings, faecal drop counts or hunting harvest which provide only relative estimates and population trends. Absolute population sizes could be yielded by a Capture-Mark-Recapture (CMR) approach. However, capturing of wild boars is difficult to realize and costly in terms of personnel and field effort. Furthermore the capture probabilities are heterogeneous due to the variable behaviour of individuals influenced by age, sex, and experience of the animals. Non-invasive genetic methods are a promising complement to the traditional methods for population size estimation particularly for wild boar. These methods reduce stress and capture bias and increase the number of re-captures. Faeces proved to be a suitable DNA source for wild boar genotyping, due to almost equal capture probability. However working with faeces implicates difficulties such as low DNA rnquality and quantity, genotyping errors as dropout and false alleles. The main aim of the present study was to develop a reliable, cost-efficient, reproducible and practicable method for wild boar genotyping. This method should provide a reliable dataset of genotypes obtained from the collected faeces samples. Individual identification forms the basis for an improved mark-recapture approach. As there is no sound method for absolute population counts in free living wild boar, reference values for the validation of this new approach are missing. Therefore, different routines to reduce and to assess genotyping errors were compared within this thesis. For maximum amplification rate, the storage, the extraction methods and the PCR-procedure were optimised. A step by step procedure was evaluated in order to determine the minimum required microsatellite (MS) number for reliable individual identification including a test with family groups (female and embryo tissue) to distinguish even between close relatives. A multiple-tubes approach, post-amplification checking and different correction procedures were applied to reduce genotyping errors. In order to quantify real genotyping error rates (GER) of datasets derived from sampling in the Palatinate Forest in western Germany, different methods for GER determination were compared with each other, obtaining GERs between 0% and 57.5%. As a consequence, more strict criteria for the multi-tube approach and increased repetition number of homozygous samples were used. An additional method validation was the implementation of a blind test to achieve the reliability of the genotyping and error checking procedure. Finally a strict and practicable proposal for the lab procedure was developed, by beginning with faecal sample collection and ending with a reliable dataset with genotypes of each sample. The results of the presented method were derived from two sampling periods in a 4000 ha area in the Palatinate Forest in Rhineland-Palatinate in December 2006 and 2007. Both provided high confidence intervals (CI) applying inaccurate estimates (eg. for 2006 population size amounted to 215 with CI 95% of 156-314 and for 2007 population size amounted to 415 with CI 95% of 318-561) due to low sampling sizes (for 2006 n = 141 and for 2007 n = 326), successfully analysed samples (for 2006 n = 89 and for 2007 n = 156) and recapture numbers (for 2006 n = 12 and for 2007 n = 24). Furthermore, the population estimates even for the lowest values were considerably higher than previously assumed by hunting statistics, which implicates an ineffective hunting regime in the study area. For the future prospect, to obtain more precise population size estimations the increase of sampling sizes is inevitable, because absolute and reliable estimates are highly desirable for wildlife management and the control of diseases transmission. Nevertheless, the method for individual genotyping of wild boars evaluated in this thesis could be successfully established resulting in reliable datasets for population estimation modelling with sufficiently low GER.