The Diffusion of Innovations theory, while one of the oldest social science theories, has embedded and flowed in its popularity over its 100 year or so history. In contrast to contagion models, diffusion of innovations can be more complex since adopting an innovation usually requires more than simple exposure to other users. At the same time, although computational tools for data collection, analysis, and network research have advanced considerably with little parallel develop of diffusion network models. To address this gap, we have created the netdiffuseR R package. The netdiffuseR package implements both classical and novel diffusion of innovations models, visualization methods, and data-management tools for the statistical analysis of network diffusion data. The netdiffuseR package goes further by allowing researchers to analyze relatively large datasets in a fast and reliable way, extending current network analysis methods for studying diffusion, thus serving as a great complement to other popular network analysis tools such as igraph, statnet or RSiena. netdiffuseR can be used with new empirical data, with simulated data, or with existing empirical diffusion network datasets.