The concern over wireless distributed networks (WDNs) such as Machine-to-Machine (M2M) systems and Internet of Things (IoT) has risen. In massive WDNs, it is important to strictly manage the interference power among wireless links: radio propagation prediction between distributed terminals is a critical issue for highly efficient spectrum use. In this paper, we propose a novel radio propagation estimation using spectrum database which collects communication results from mobile terminals. The proposed method focuses on the spatial-correlation of radio propagation characteristics between different wireless links. Using maximum likelihood-based pathloss estimation and Kriging-based shadowing estimation, the radio propagation of the wireless link that has arbitrary location relationship can be predicted. From numerical results, it is shown that the proposed method achieves higher estimation accuracy than the conventional pathloss-based estimation methods. Furthermore, we show that the proposed technique can predict the probability density function (PDF) of the estimation error.