Seed long-distance dispersal (LDD) is essential to explain plant migration. However, few studies have addressed the magnitude and frequency of LDD events given the difficulty of measuring them in situ. Computational simulation offers an alternative to the in situ methods. In this study we proposed a simulation model of seed dispersal for two anemochoric conifers, which includes wind patterns, seed and tree traits. We proposed and measured 18 dispersal traits for Abies religiosa and Pinus hartwegii and analyzed variation between traits and species through a principal component analysis. We used the Weather Research and Forecasting (WRF) atmospheric simulation model to obtain wind speed and direction data at the study zone (Iztaccihuatl volcano, central Mexico). We performed linear regression models to simulated seed dispersal events considering horizontal wind speed, seed traits and seed release height, and using a mechanistic model, we integrated vertical wind speed and wind direction. Seeds of both species presented similar morphology but were sorted into two groups. The relationship between wing size and seed weight may be a key element to dispersal, as it influences the interaction of the seed with the wind. Although we expected that P. hartwegii, seed traits and higher distribution would promote more and longer LDD events, A. religiosa presented more and longer LDD. The maximum dispersal distance was 105 m for A. religiosa and 64 m for P. hartwegii. Both species showed differences in dispersal capacity, which may be related to their seed traits. The frequency of LDD events indicates that a low proportion of seeds would travel more than 20 m away from the parent tree. This suggests that, under migration scenarios, new trees movement up would take place gradually.