Assessing speech intelligibility for individuals with dysarthria is critical for understanding the severity of motor speech disorders and evaluating speech therapy interventions. Traditional subjective as- sessments, while effective, are resource-intensive and prone to bias, which highlights the need for reliable objective measures. This study investi- gates the applicability of MIKNN (Mutual Infor- mation with K-Nearest Neighbors) as an objective speech intelligibility measure for dysarthric speech, by comparing objective intelligibility scores with subjective ratings. Unlike its proven effective- ness with neurotypical speech, the performance of objective measures on atypical speech, such as dysarthria, remains under-explored. The study compares MIKNN with state-of-the-art measures, including P-STOI and P-ESTOI, using the UA- Speech dataset. Key challenges addressed in- clude adapting MIKNN to handle the temporal and spectral variability inherent in dysarthric speech. The results demonstrate that while MIKNN offers promising correlations with subjective scores, it is outperformed by P-STOI and P-ESTOI.