Investing in early childhood development (ECD) is critical for individual and societal development. Variable-centered research on ECD has shown that family wealth, maternal education, and parenting practices predict childhood outcomes overall. However, little is known about differences in the ECD patterns and their predictors. This study examined the latent classes of ECD using data from three waves of the Multiple Indicators Cluster Surveys (MICS) conducted in 29 low- and middle-income countries (LMICs) between 2010 and 2020 (MICS 4, 5, and 6) and identified their predictors at different ecological levels. The total sample size for analyses was 226,374 (n = 70,082, n = 91,652, n = 64,640; M = 47.23(months), SD = 6.87). Three classes, Learning Challenged but On Track for Physical and Social-emotional Development, Academically Challenged but Approaches-to-Learning Competent, On Track for Physical and Social-emotional Development, and Competent across All Domains, were consistently identified across MICS 4–6 using latent class analysis. Three variables, all at the microsystem level, predicted class membership with acceptable effect sizes in one or more waves of the MICS data: preschool attendance, number of books at home, and maternal education. The study has implications for future research and the development of policies aimed at monitoring and supporting ECD in LMICs.