SETTING: In many high tuberculosis (TB) burden countries, there is substantial geographical heterogeneity in TB burden. In addition, decisions on TB funding and policy are highly decentralised. Subnational estimates of burden, however, are usually unavailable for planning and target setting.OBJECTIVE and DESIGN: We developed a statistical model termed SUBsET to estimate the distribution of the national TB incidence through a weighted score using selected variables, and applied the model to the 514 districts in Indonesia, which have substantial policy and budgetary autonomy in TB. Estimated incidence was compared to reported facility and domicile-based notifications to estimate the case detection rate (CDR). Local stakeholders led model development and dissemination.RESULTS: The final SUBsET model included district population size, level of urbanisation, socio-economic indicators (living floor space and high school completion), human immunodeficiency virus prevalence and air pollution. We estimated district-level TB incidence to be between 201 and 2,485/100 000/year. The facility-based CDR varied between 0 and 190%, with high variation between neighbouring districts, suggesting strong cross-district health utilisation, which was confirmed by domicile-based CDR estimation. SUBsET results informed district-level TB action plans across Indonesia.CONCLUSION: The SUBsET model could be used to estimate the subnational burden in high-burden countries and inform TB policymaking at the relevant decentralised administrative level.