Monitoring has become an integral part of many restoration projects and is a ready source of big data to parameterize forecasting models. The spatial and temporal breadth of monitoring data provides opportunities to investigate ecological processes on scales unfeasible for experimental manipulations. While there are difficulties associated with using monitoring data, including confounding factors, non-random placement of restoration treatments, and pseudoreplication, it is often the only available data for understanding processes at large spatial and temporal scales. Integrating knowledge derived from past restoration efforts into forecasts of success for future restoration projects will be a key aspect of adaptive management. This session will explore the use of monitoring and management data to inform restoration predictions in sagebrush steppe, grasslands, and prairies. There are a wide range of data that can be leveraged, including historic data on land treatments and routine monitoring data (including long term time series). We will consider the barriers associated with using monitoring data, transferability of predictions from one site to another, upscaling predictions by using multiple sources of data, and lessons learned on predicting restoration success from past analyses. The session will comprehensively address challenges and opportunities for forecasting in ecological restoration. Given high variation of restoration outcomes, the accuracy of predictions could vary depending on spatial, temporal, and biological scales. The session will integrate scientific insights about predictions of species populations, functional groups, and communities, including humans as an inherent part of modern ecosystems. Spatial and temporal transferability of results represents another challenge in restoration, however, is an essential component of ecological predictions. Finally, we will share perspectives on developing an iterative process of data collection and model validation to link restoration ecology with ongoing land management.