Structural and pragmatic language deficits are core symptoms of Autism Spectrum Disorder (ASD) and predict long-term outcomes. Clinical measurement of language proficiency is cumbersome and costly; however, Automated Language Measures (ALMs) can be automatically calculated from language samples. Objectives: 1. examine language differences between three clinical groups (ASD, Attention Deficit Hyperactivity Disorder (ADHD), and Typically Developing (TD)); 2. analyze the convergent validity of these measures by calculating correlations between the ALMs and standardized language measures; 3. investigate the accuracy of each individual ALM in predicting ASD status; and 4. investigate any gains in accuracy obtained by combining all ALMs together to predict ASD status.