This study explores the development of expressive language disorder in a five-year-old child from the perspective of a parent in Bandung Regency, Indonesia. Using a descriptive qualitative case study approach, the research follows the child’s developmental history from the prenatal period through the age of five. Data were collected through in-depth interviews conducted between January and April 2024, using version D of the Speech Participation and Activity Assessment of Children (SPAA-C) instrument. The analysis employed a descriptive analytical method, including data reduction, data presentation, triangulation, and conclusion drawing. Findings indicate that the child’s expressive language delay is influenced by a combination of prenatal, perinatal, and environmental factors. The child was born prematurely and spent the first 43 days in an incubator, resulting in limited sensory stimulation during a critical developmental window. Prenatal risk factors such as intrauterine growth restriction (IUGR), fetal distress, and severe preeclampsia (PEB) were also identified. Perinatal complications, including intestinal infection, further disrupted early feeding and sensory experiences. Environmental factors such as limited interaction during the COVID-19 pandemic, extended family misconceptions about developmental red flags, inconsistent nutritional intake, and maternal psychological stress contributed to delays in expressive language development. Despite these challenges, the child demonstrated strong receptive language skills, age-appropriate cognitive development, and positive social functioning. This research provides context-specific insights into how expressive language disorders manifest and are managed in a non-clinical, culturally embedded setting in Indonesia. The findings have practical implications for early childhood education (ECU), particularly in informing inclusive teaching strategies for children with expressive language delays. Future research is recommended to explore classroom-based intervention strategies and to extend analysis across broader populations, including variables such as genetics, gender, cognitive profiles, birth order, and socioeconomic status.