Abstract: Gas–liquid two-phase flow is ubiquitous in energy and process industries, and accurate online measurement of void fraction is essential for predicting pressure drop, heat and mass transfer, and ensuring safe operation. This study proposes a method for quantifying bubble void fraction in gas–liquid two-phase flow using electrical resistance tomography (ERT). To meet the requirements of real-time characterization a full-cross-section, time-varying measurement framework based on ERT was established. The complete electrode model and linear back-projection (LBP) algorithm were employed to regularize and reconstruct conductivity distributions, from which both local and overall void fractions were calculated. Based on the acquired ERT data, the relationship between bubble void fraction and bubble velocity was further established, and the calculated results show good agreement with three classical void-fraction models, namely the Maxwell-Garnett, Bruggeman, and drift-flux models. The findings demonstrate that ERT can provide comprehensive, non-intrusive data support for two-phase flow monitoring, flow regime identification, and parameter optimization, offering a reliable technical approach for online void-fraction quantification and process optimization. This method provides a theoretical basis and data support for online monitoring and intelligent control of gas-liquid two-phase flows in industrial processes.