The study was focused on assessing the determinants of tax productivity performance in Tanzania adopting a time series analysis based on data spanning from the year 1996 to 2020. A time series using the multivariate regression model of the Ordinary Least Square Method (OLSM) was employed to analyze the data. The findings of the study show that GDP as a proxy of economic factors, the share of agriculture in GDP as a proxy of structural factors and regulatory quality as a proxy of institutional factors have a positive significant relationship with the dependent variable (i.e., total tax as a percent of GDP). On the other hand, the industrial sector, trade volume (i.e., export and import), and control of corruption were insignificant factors influencing the dependent variable (i.e., total tax as a percent of GDP). As part of the policy implication, we recommend that there should be sustainable initiatives to formalize the agricultural sector. Improve the industrial sector, trade volume and institutional environment to widen the tax base and increase tax revenue to align with the country’s economic development.