The shortfin mako shark, Isurus oxyrinchus (SMA), is a highly migratory pelagic species found globally. It is particularly vulnerable as bycatch in longline fisheries, and has a vulnerable status according to the IUCN. SMA is considered a data-limited stock as there is incomplete catch information, limited information on the catch composition (size frequencies), and few abundance indices (e.g., standardised CPUE series). A preliminary stock assessment was performed by Brunel et al. in 2018 for the IOTC convention area using CMSY, a catch-only method, and a built-in Bayesian surplus production model (BSM), based on reconstructed catch data and standardised CPUEs from the EU longline fleet of Spain (2006-2016), and Portugal (2000-2016). This preliminary assessment found that SMA had been experiencing overfishing from the 1990s (F/Fmsy =2.57), but that the biomass of the stock was decreasing but not overfished (B2015/Bsmy close to 1). Here, we showcase the FAO Sustainable Development Goal (SDG) 14.4.1 Stock Monitoring Tool, which is available online on the SDG 14.4.1 Virtual Research Environment. This R-Shiny tool was developed to support countries in performing data-limited stock monitoring of their fisheries resources to aid in their reporting for the SDG Indicator 14.4.1 - Proportion of biologically sustainable stocks. We highlight the utility of this tool by performing a preliminary stock assessment for SMA using the CMSY catch-only and BSM method available via the Tool, providing background and advice in parameterising the model. To support the SMA assessment, we also run JABBA (Winker et al. 2018), a method not available on the Tool, to compare to the CMSY results. Contrary to Brunel et al, we use nominal catch of SMA (1964-2018) and scaled CPUEs from Japan (1993-2018), Spain (2001-2018), Taiwan (2005-2018), and Portugal (2000-2018). Catch ratio between SMA catch and target species catch as used in Brunel et al. were not available at the time of the stock assessment. We develop a demographic analysis based on Leslie Matrices to determine a prior for r (resilience, or intrinsic growth rate). We find that CMSY, BSM, and JABBA give consistent results in terms of reference points, which indicate that SMA is experiencing overfishing (F/Fmsy well above 1) but is not overfished (most results indicate B/Bmsy > 1). As JABBA can take into account all CPUEs to inform the stock assessment, we define these model outputs as our best case scenario. The projections are run and provided for this model. We include an appendix of a step-by-step guide to support the Stock Monitoring Tool.