This paper takes stock of methods toprofile the unemployed in public employment services (PESs)in OECD countries, in order to single out suitableapproaches for PES in emerging economies. Profiling shouldenable PESs to segment jobseekers into groups with similarrisk of work-resumption, and in turn to determine theirlevel of access to different levels of treatment. In ourframework PESs rely to a varying extent on (i) case workerdiscretion and on (ii) data-intensive approaches. On onehand of the spectrum, PESs may allocate interventions on afirst-come-first-serve basis according to broad eligibilitycriteria (age, unemployment duration). This is likely toeither induce deadweight loss or to delay treatment. Mostoften case managersjudgment, steered by qualitativeguidelines, also plays a role. In this case outcomes dependstrongly on the available time and capacity of casemanagers. An alternative approach is to exploit data aboutjobseekers to determine the probability of work-resumptionaccording to a statistical model, which then allows theidentification of customers most likely to need active labormarket interventions. We argue that for PES in emergingeconomies that show limited case management experience andhigh customer load, statistical profiling could be asuitable tool to maximize the impact of their scarce resources.