Objective: To summarize available chronic kidney disease (CKD) diagnostic and prognostic models in Low- and Middle-Income countries (LMIC) Method: Systematic review (PRISMA guidelines). We searched Medline, EMBASE, Global Health (these three through OVID), Scopus and Web of Science from inception to April 9th, 2021, April 17th, 2021 and April 18th, 2021, respectively . We first screened titles and abstracts, and then studied in detail the selected reports; both phases were conducted by two reviewers independently. We followed the CHARMS recommendations and used the PROBAST for risk of bias assessment. Results: The search retrieved 14,845 results, 11 reports were studied in detail and nine (n= 61,134) were included in the qualitative analysis. The proportion of women in the study population varied between 24.5%-76.6%, and the mean age ranged between 41.8-57.7 years. Prevalence of undiagnosed chronic kidney disease ranged between 1.1%-29.7%. Age, diabetes mellitus and sex were the most common predictors in the diagnostic and prognostic models. Outcome definition varied greatly, mostly consisting of urinary albumin-to-creatinine ratio and estimated glomerular filtration rate. The highest performance metric was the negative predictive value. All studies exhibited high risk of bias, and some had methodological limitations. Conclusion: There is no strong evidence to support the use of a CKD diagnostic or prognostic model throughout LMIC. The development, validation and implementation of risk scores must be a research and public health priority in LMIC to enhance CKD screening to improve timely diagnosis.