This present scientific and technological research was aimed at showing that time series represent an excellent tool for data traffic modelling within Wi-Fi networks. Box-Jenkins methodology (described herein) was used for this purpose. Wi-Fi traffic modelling through correlated models, such as time series, allowed a great part of the data's behavioral dynamics to be adjusted into a single equation and future traffic values to be estimated based on this. All this is advantageous when it comes to planning integrated coverage, reserving resources and performing more efficient and timely control at different levels of the Wi-Fi data network functional hierarchy. A six order ARIMA traffic model was obtained as a research outcome which predicted traffic with relatively small mean square error values for an 18-day term.