Coastal small-scale fisheries remain largely unassessed and unregulated worldwide, which leads to a high risk of overfishing. Availability and quality of data are major barriers to performing model-based assessments, particularly in low and middle-income countries. In that context, alternative assessment methods are key to defining priorities, as well as prompting and guiding management actions. In this study, we assessed the vulnerability to overfishing of 10 extremely data-poor species of coastal groundfish in Peru, by applying an adapted Productivity Susceptibility Analysis (PSA). We classified fisheries-related Susceptibility attributes and streamlined a process to assess and integrate multiple fisheries and gears into a single score for each attribute. The data quality scores regarding productivity and susceptibility were between “limited” and “no data”, across all stocks. Therefore, expert knowledge was key for completing the assessment. Stocks of four species presented extremely high Vulnerability to overfishing: broomtail grouper (V=2.57), grape-eye seabass (V=2.50), pacific goliath grouper (V=2.28) and galapagos sheephead wrasse (V=2.24). Three showed high Vulnerability to overfishing: black snook (V=2.13), harlequin wrasse (V=2.05) and chino (V=2.01). Two showed medium Vulnerability to overfishing: mulata (V=1.89) and pacific beakfish (V=1.89). Only the stock of bumphead parrotfish showed low Vulnerability to overfishing (V=1.73). We contrasted the resulting Vulnerability scores with the limited available information on the statuses of these stocks, to evaluate the accurateness of the overfishing probability thresholds proposed in PSA literature. We found that Vulnerability scores were mostly consistent with contrasted information and that the thresholds remain useful to inform fisheries management in extremely data-poor contexts. Our results shed light on the need for the implementation of fishing regulations and the generation of biological and fishery-related data on coastal groundfish in Peru.