Fish school descriptors extracted from omnidirectional multi-beam data are biased due to beam width-related effects, and echotraces are distorted in a range-dependent manner that is a function of transducer intrinsic properties, as well as fish school characteristics. This work investigates a simulation approach that models the three-dimensional insonification of fish schools by an omnidirectional fishery sonar in order to assess the bias in measuring two key morphometric and energetic descriptors, namely the horizontal cross-sectional area of schools and their mean volume backscattering strength. Simulated fish schools of different sizes and backscattering properties were insonified at various ranges from the multi-beam transducer, outputting volume backscattering strength echograms. The simulated data were used to develop empirical models that correct the examined descriptors using only information extracted from the observed echotraces. Depending on the difference between the observed mean volume backscattering strength of a school and the echogram processing threshold, mean absolute percentage errors in measured area and volume backscatter reduced from 100.7% and 79.5% to 5.2% and 6.4%, respectively. The mean volume backscattering strength of a school is a key parameter for obtaining fish density estimates, and the results highlight the need for descriptor corrections to better interpret the multi-beam data.