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Carrion beetles are an important part of the decomposition processes in the ecosystems of the North Hemisphere. Along with the flies, they are the main consumers of dead animal tissues, thus driving the nutrients from the carcass to other parts of the ecosystem. These animals can also be used as bio-indicators in forensic entomology, where they help to identify the time of the death and post-mortem body manipulation. However, for using the beetles in this manner, it is essential to identify seasonal cycles in the life of these beetles and their spatial distribution. This knowledge will allow the detection and explanation of anomalies in the composition of the fauna on a dead body, or it can be used for testing dubious zoological records. Both our study subjects, Necrodes littoralis and Thanatophilus rugosus, are considered to be potentially useful indicators, since they are frequent on carrions of large animals including humans. However, the information about their ecology is either limited or outright anecdotal and not backed up by real and unbiased data. Especially spatial distribution can be a subject to strong bias, because collectors visit localities where the species has already been confirmed with higher probability than it would be expected at random. Furthermore, the presence of roads, human settlements or natural phenomena like rare or charismatic species can increase collectors' activity and thus the probability of detecting the species. To evaluate the seasonal activity and spatial distribution statistically, we used data from several sources including museums and private collections to combine them into an extensive database. Only the data from the Central European countries were used to avoid introducing local adaptation effects and clinal variability from the countries outside of our focal area. MaxEnt algorithm with environmental filtering was used to model the unbiased probabilistic occurrence of the two species. The precision and accuracy of the model was tested on an independent dataset that was not used for modeling, to reveal possible model overfit. We believe that the results we present will allow for testing for anomalies in the occurrence of N. littoralis and T. rugosus, thus enabling evaluation of dubious zoological records, and be further used in forensic entomology. [ABSTRACT FROM AUTHOR]