Indicators of academic achievement for bilingual students can be inaccurate due to linguistic heterogeneity. For indigenous populations, language shift (the gradual replacement of one language by another) is a factor that can increase this heterogeneity and poses an additional challenge for valid testing. We investigated whether and how indigenous populations can be validly included in a large-scale assessment program. We gave Mexican preschool Mayan students aged 5 to 6 years the same set of mathematics items in three versions: (1) original in Spanish, (2) Mayan translation, and (3) content equivalent, developed from scratch in Mayan. Also, we collected information on the students' and the teachers' use of Spanish and Mayan, and on the communities' support of the two languages. Students performed poorly on the three versions. Generalizability theory-based analyses revealed considerable performance inconsistency across items and language versions and low generalizability and dependability coefficients. This performance instability appears to stem from a dwindling support of the Mayan language in Mayan schools and communities. Fair, valid assessment of indigenous populations in either their languages or their countries' dominant languages appears to be difficult to accomplish with current testing models and policies.