Introduction: Diffusion can efficiently detect infratentorial and brainstem infarctions. Fluid-attenuation Inversion Recovery (FLAIR) is a widely used Magnetic Resonance Imaging (MRI) technique for the segmentation of brain lesions and strokes. Aim: To investigate the sensitivity of the Lesion Prediction Algorithm (LPA) within the Lesion Segmentation Tool (LST) in the automated segmentation of acute and subacute brainstem infarctions. Materials and Methods: This study was a retrospective diagnostic accuracy study where 24 patients with brainstem infarctions were referred from the Emergency Department to the Department of Radiodiagnosis at Kasr Alainy Hospital, Cairo University, Egypt. The study was conducted from September 2016 to June 2023. It included 24 patients (14 males and 10 females) with acute and subacute brainstem infarctions. MRI of the brain and diffusion were performed on all patients. Automated segmentation of brainstem infarctions using FLAIR was conducted in all cases. Manual and segmented volumes of brainstem infarctions were calculated. Sensitivity and accuracy of the LPA within the LST in automated segmentation of acute and subacute brainstem infarctions were evaluated. Pearson correlation was used to correlate volumes of White Matter Lesion (WML) burden in patients with brainstem infarctions and patients’ age. Results: The mean age of the participants was 51.75±11.95 years. The sensitivity of the LPA in automated segmentation of acute and subacute brainstem infarctions was 63.6% and 76.9%, respectively. An insignificant correlation (r=0.08; p-value=0.68) between the volumes of WML burden in patients with brainstem infarctions and patients’ age was noted. Conclusion: The sensitivity of the automated method in the segmentation of subacute brainstem infarctions was higher than that in acute brainstem infarctions.