Macrophytes and seagrasses play a crucial role in a variety of functions in marine ecosystems and respond in a synchronized manner to a changing climate and the subsequent ecological status. The monitoring of seagrasses is one of the most important issues in the marine environment. One rapidly emerging monitoring technique is the use of acoustics, which has advantages compared to other remote sensing techniques. The acoustic method alone is ambiguous regarding the identities of backscatterers. Therefore, a computer program package was developed to identify and estimate the leaf biometrics (leaf length and biomass) of one of the most common seagrasses, Posidonia oceanica. Some problems in the acoustic data were resolved in order to obtain estimates related to problems with vegetation as well as fisheries and plankton acoustics. One of the problems was the “lost” bottom that occurred during the data collection and postprocessing due to the presence of acoustic noise, reverberation, interferences and intense scatterers, such as fish shoals. Another problem to be eliminated was the occurrence of near-bottom echoes belonging to submerged vegetation, such as seagrasses, followed by spurious echoes during the survey. The last one was the recognition of the seagrass to estimate the leaf length and biomass, the calibration of the sheaths/vertical rhizomes of the seagrass and the establishment of relationships between the acoustic units and biometrics. As a result, an autonomous package of code written in MATLAB was developed to perform all the processes, named “POSIBIOM”, an acronym for POSIdonia BIOMass. This study presents the algorithms, methodology, acoustic–biometric relationship and mapping of biometrics for the first time, and discusses the advantages and disadvantages of the package compared to the software dedicated to the bottom types, habitat and vegetation acoustics. Future studies are recommended to improve the package.