the monte carlo method based on eclectic data as an efficient tool for predictions of endpoints for nanomaterials two examples of application the theoretical predictions of endpoints related to nanomaterials are attractive and more efficient alternatives for their experimental determinations such type of calculations for the usual substances ie non nanomaterials can be carried out with molecular graphs however in the case of nanomaterials descriptors traditionally used for the quantitative structurepropertyactivity relationships qsprsqsars do not provide reliable results since the molecular structure of nanomaterials as a rule cannot be expressed by the molecular graph innovative principles of computational prediction of endpoints related to nanomaterials extracted from available eclectic data technological attributes conditions of the synthesis etc are suggested applied to two different sets of data and discussed in this work