Success of ecological restoration is often only knowable if treatments meet criteria defined by biotic thresholds, but analytical frameworks to determine metrics of success and their underlying thresholds are needed. Early indicators of longer-term recovery trajectories are particularly critical where re-treatments may be required, such as in harsh climates or where repeated disturbances or invasive pressures prevail. We developed a framework for identifying which biotic traits would provide the best initial indication of longer-term target restoration goals and applied the framework to restoration drill-seedings of deep-rooted perennial bunchgrasses (DRPBGs) used to rehabilitate and restore semiarid rangelands threatened by exotic annual grasses (EAGs, e.g. cheatgrass) and the recurrent wildfire that EAGs cause. Initial traits measured included cover, basal diameter, height, and density (#plants/area) of DRPBGs and cover of EAGs and Sandberg bluegrass (Poa secunda, POSE, a disturbance-adapted perennial). The longer-term target objective was ≥25 % DRPBG cover and ≤13 % EAG cover by the 5th year following drill-seedings. Measurements were made on 112 plots spanning 113,000 ha in sagebrush steppe on the Soda wildfire scar, in the Northern Great Basin, USA. Traits of DRPBGs tended to be uncorrelated with one another, thus each was informative in describing vegetation condition. Where DRPBG cover was initially >17 %, it tended to become >25 % by the 5th-year post-seeding. In plots that overcame an initial risk of not meeting the target objective (i.e. <17 % initial DRPBG cover), DRPBG tended be large DRPBGs (>22.8 cm height) and plots also had >7 % cover of POSE. Additional “sets” of initial vegetation traits were also predictive of longer-term restoration success or failure. Restoration drill-seeding of DRPBGs is a key but varied-outcome tool for breaking the exotic grass-fire cycle, and, contrary to a conventional tendency to rely on a limited number of mean traits such as % cover, a suite of biotic traits appears necessary to monitor to reliably know if trials are likely to yield success.