Data-limitation is a difficult issue in fishery stock assessment and management. Base on length frequency data of Parargyrops edita collected from otter trawl survey in the Beibu Gulf in 2006–2018, we used length-based Bayesian biomass (LBB) method to estimate population parameters, namely asymptotic length (L∞), optimal length-at-first-capture (Lc_opt), relative natural mortality (M/k), and relative fishing mortality (F/k). The L∞ was estimated to be 21.0 cm, Lc_opt to be 12.6 cm, and M/k, F/k, Z/k and E to be 1.49, 3.65, 5.15, and 0.67, respectively. L∞ and Lc_opt showed the similar downward trend, and fish growth tended to be increasing. The Lc_opt and exploitation rate estimated by LBB were close to those estimated by independent full stock assessments. This case study suggested that if the length frequency represents length composition of a stock, the estimation by LBB will perform properly, and the method based on LBB can provide informative reference for fishery stock assessment under the data-limited conditions.