The access to real geometallurgical block models is very limited in practice, making difficult for practitioners, researchers and students to test methods, models and reproduce results in the field of geometallurgy. The aim of this work is to propose a methodology to simulate synthetic geometallurgical block models with geostatistical tools preserving the coherent relationship among primary attributes, such as grades and geology, with mineralogy and some response attributes, for example, grindability, throughput, kinetic flotation performance and recovery. The methodology is based in three main components: (i) multivariate geostatistics, (ii) froth flotation simulation models, and (iii) well known performance plant parameters. The simulated geometallurgical block models look very realistic, and they are coherent in terms of geology and mineralogy, and processing metallurgical performance responses are consistent with what is seen in practice. These simulations can be used for several proposes, for example, benchmarking geometallurgical modelling methods and mine planning optimization solvers. Simulations at small scales also serve to represent drill holes campaigns and generate sample dataset incorporating geometallurgical attributes and real spatial variability. The methodology is completely reproducible with no use of proprietary models or methods. Implementations of all methods can be found in public domain software, and different ore body types may be incorporated with little effort.