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Estimating transmission rates is a challenging yet essential aspect of comprehending and controlling the spread of infectious diseases. There are various methods available for this purpose, each with its own assumptions, data requirements, and limitations. This paper introduces a phylogenetic approach called transRate, designed to estimate inter-population transmission rates. The phylogenetic method, which maintains statistical consistency under the multi-population Susceptible-Infected-Recovered (SIR) model, integrates genetic information with traditional epidemiological approaches. This integration improves the accuracy of transmission rate estimates, facilitating more effective disease control and prevention strategies. Simulation analyses validate the precision of transRate in estimating transmission rates. With the growing abundance of public databases for genomic sequences, transRate is becoming more prevalent in tracking and preventing the spread of such diseases.