Purpose: Previous investigations reveal that children with attention-deficit/hyperactivity disorder (ADHD) produce elevated rates of linguistic mazes (i.e., filled pauses, repetitions, revisions, and/or abandoned utterances) in expressive language samples (Redmond, 2004). The current study aimed to better understand maze use of children and adolescents with ADHD with a focus on the specific maze types produced in different language sampling contexts based on the Autism Diagnostic Observation Schedule (ADOS-2; Lord et al., 2012). Method: Participants included twenty-five 4- to 13-year-olds with a confirmed diagnosis of ADHD. Each participant completed the ADOS to provide narrative and conversational language samples. Research assistants transcribed at least 100 utterances from the ADOS using Systematic Analysis of Language Transcripts (Miller & Chapman, 2000) conventions. Dependent variables included the rates of repetitions, revisions, filled pauses, content mazes (Thordardottir & Ellis Weismer, 2002), and stalls (Rispoli, 2003; Rispoli, Hadley, & Holt, 2008) produced in narrative and conversational portions of the ADOS. Results: In the full sample, participants produced a significantly greater rate of revisions than filled pauses (p = 0.01) and repetitions (p < 0.01). Participants also produced a significantly lower rate of filled pauses than content mazes (p < 0.01). Across contexts, participants produced a higher rate of filled pauses in conversational versus narrative contexts. Age was positively correlated with revisions and content mazes. Mean length of utterance was positively correlated with revisions, repetitions, and context mazes. Expressive language ability was positively correlated with filled pauses and stalls. Conclusion: The children and adolescents in our sample demonstrated a unique profile of maze use. Sampling context had a limited influence on maze use, whereas maze use was impacted by age, mean length of utterance, and expressive language ability. Study findings highlight the importance of analyzing maze types separately rather than as a single category.