School reopening during an Ebola outbreak is often framed as a binary question of whether schools are safe. For Ebola, however, the immediate operational question is where an infected school-age child may reach the school system before recognition and isolation, and whether local systems can detect and respond rapidly. We developed an exploratory, scenario-based health-zone framework for the September 2026 rentree during the ongoing Bundibugyo virus disease outbreak in eastern Democratic Republic of the Congo. The primary estimand was scenario-based expected introduction pressure, expressed on an expected-count scale, for infected school-age children reaching school in each health zone during a one-week window. The framework combined recent reported transmission, estimated school-age exposure and attendance, a surveillance/interception probability, and directed mobility-based importation. Case-fatality patterns were analysed separately and did not determine introduction pressure. A 10,000-draw probabilistic sensitivity analysis examined uncertainty in the school-age case share, attendance, pre-isolation school-entry probability and mobility scaling. Geographic components were retrospectively evaluated at eight non-overlapping weekly origins from 1 June to 20 July 2026, using subsequent reported seven-day health-zone activity and first reported cases in previously unaffected zones as outcomes. Seven-day local epidemic pressure discriminated health zones with subsequent reported activity with pooled ROC-AUC 0.848; the 14-day local measure increased this to 0.885. Adding directed mobility increased ROC-AUC to 0.952. In the base scenario, the six-province combined scenario-based expected introduction pressure was 10.97; the probabilistic sensitivity median was 11.17, with a 2.5-97.5% sensitivity range of 5.56-20.97. Bunia, Rwampara and Nizi had the highest base introduction pressures, followed by Katwa and Nia Nia. Among 24 previously unaffected health zones that subsequently reported a first confirmed case, 13 (54.2%) were in the top 10 and 18 (75.0%) in the top 20 mobility-ranked zones; random selection would have been expected to capture approximately 2.05 and 4.10 events, respectively. In a separate six-origin exploratory nested-specification sensitivity, surveillance/access modifiers did not improve geographic discrimination over local epidemic pressure alone, whereas mobility did. The dominant structural uncertainty remained the probability that an infected child reaches school before being identified. The framework supports targeted geographic prioritisation and minimum school-health readiness, but its probabilities are model-implied scenario probabilities rather than calibrated forecasts or evidence for a single national open/close decision.