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Abstract: Catch and effort data form an important, and often the only, source of data for stock assessment and management of marine resources in developing countries. Population parameters and management quantities important for stock assessment are often estimated by fitting production models to standardized series of catch-per-unit-effort (CPUE). Such basic information is notoriously hard to obtain for small-scale fisheries because of the large spatial and temporal variability in effort, numerous landing sites, and limited access for biological data collections. In this paper, we present a probability-based survey sampling method for the monitoring of the small-scale fisheries in Mozambique. The survey is an on-site intercept design, which supports the estimation of annual catch and effort and other key statistics for the coastal fisheries in a sampled geographic area. Estimates of catch and effort, with associated relative standard errors, for beach seine fisheries in the district of Angoche and for Inhambane Bay are used to illustrate the applicability of the methodology. The flexible survey design is nowadays used to monitor small-scale fisheries in all provinces of Mozambique. We also present a method for obtaining approximate estimates of total catches for a study area when the coverage of fishing centers is incomplete. Survey estimates of the average proportion of beach seines that are actively used in fishing by month are used to adjust fishing effort derived from census data on the total number of beach seines for fishing centers not covered in the survey. The adjusted effort is then combined with estimates of CPUE to estimate the total catches for fishing centers that are not covered in the survey. Results suggest that the common method (often referred to as a frame survey) for studying artisanal fisheries that relies on effort estimates from a census of landing sites at some intervals in time, combined with CPUE from regular sampling from a small subset of fishing centers selected ad-hoc would introduce substantial bias of variable magnitude. The reason is that effort in small-scale fisheries strongly depends on weather conditions and socio-economic factors. [Copyright &y& Elsevier]