We propose a method by which the thermal conductivity of a nanostructure with arbitrary geometry can be predicted through Monte Carlo sampling of the free paths associated with phonon-phonon and phonon-boundary scattering. The required inputs are the nanostructure geometry and the bulk phonon frequencies, group velocities, and mean free paths. The method is applied to a thin film in the in-plane and cross-plane directions and to a polycrystalline bulk material. For the film, a faster approach to the bulk thermal conductivity is found compared to predictions made using the Matthiessen rule with the bulk mean free path and an average phonon-boundary scattering length. As the dimensions of electronic, optoelectronic, and energy conversion devices are reduced, the thermal conductivities of the device components (e.g., thin films and nanowires) are also reduced. 1-11 The large electrical power densities in such devices cause Joule heating and the reduced thermal conductivities can lead to high operating temperatures, sub-optimal performance, and poor reliability. Predicting the thermal conductivity reduction in nanostructures is thus a critical part of developing next-generation thermal management strategies.We focus here on semiconducting and insulating nanostructures, where phonons (quantized lattice vibrations) dominate thermal transport. 12 As a nanostructure gets smaller, its thermal conductivity is reduced due to more frequent scattering between phonons and the system boundaries. 1-11 For very small systems (e.g., silicon films thinner than 20 nm), changes in the phonon density of states also affect thermal transport. 2,6,8 Our interest here is nanostructures large enough that the phonon density of states is bulk-like.The thermal conductivity, k, of a nanostructure in the n direction can be predicted from, 12