Low-flow analysis is important for management of water supply and droughts, determining the health of ecosystems, and for sustained agriculture. Two entropy-based methods, the ordinary entropy (ENT) method and the parameter space expansion method (PSEM), are employed for estimating parameters of the extended Burr III distribution, which is useful for low-flow frequency analysis. With parameters estimated in this manner, the extended Burr III distribution is applied to six low-flow datasets, and quantiles (discharges) corresponding to different return periods are computed. These return periods are then compared with those when the extended Burr III distribution parameters are estimated using the methods of moments (MOM), probability weighted moments (PWM), and maximum likelihood estimation (MLE). It is shown that PSEM yields the same quantiles as does MLE for discrete cases, while ENT is found comparable to MOM and PWM. The quantile (discharge) values estimated by the four methods are close to each other for smaller return periods, but large differences occur for long return periods.