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Diagnostics and supportive care for patients with non-Hodgkin lymphoma (NHL) in lower- and middle-income countries (LMICs) are lacking. We hypothesized that high-throughput transcription-based diagnostics could classify NHL specimens from Malawi amenable to targeted therapeutics. We established tissue microarrays and classified 328 cases diagnosed by hematoxylin and eosin as NHL at University of Malawi College of Medicine using immunohistochemistry (IHC) for conventional markers and therapeutic targets. A subset was analyzed using NanoString-based expression profiling with parsimonious transcriptional classifiers. Overall, 72% of lymphomas were high-grade B-cell tumors, subsets of which were enriched for expression of MYC, BCL2, and/or PD-L1. A 21-gene transcriptional classifier, previously validated in Western cohorts, divided 96% of diffuse large B-cell lymphomas (DLBCLs) with 100% of B-cell lymphomas, unclassifiable, into 1 cluster and 88% of Burkitt lymphomas into a separate cluster. Cell-of-origin categorization of 36 DLBCLs by NanoString lymphoma subtyping test (LST) revealed 69% concordance with IHC. All discordant cases were classified as germinal center B cell-like (GCB) by LST but non-GCB by IHC. In summary, utilization of advanced diagnostics facilitates objective assessment and segregation of biologically defined subsets of NHL from an LMIC without expert review, thereby establishing a basis for the implementation of effective and less toxic targeted agents.