Social network data is often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD) – responses to questions of the form “how many of your links have trait k?” Our method uses ARD to recover parameters of a network formation model, which permits the estimation of any arbitrary node- or graph-level statistic. We characterize both theoretically and empirically for which network features the procedure works. In simulated and real-world graphs, the method performs well at matching a range of network characteristics. We replicate the results of two field experiments that used network data, and draw similar conclusions with ARD alone.