The diagnosis of Amyotrophic Lateral Sclerosis (ALS) primarily relies on clinical findings and remains challenging, particularly in the early stages of the disease, where characteristic symptoms may be subtle and nonspecific. Therefore, the development of disease-specific and clinically validated biomarkers is crucial to enhance diagnostic precision and optimize patient management. Here, we explored tear fluid (TF) as a promising biomarker source for ALS, given its accessibility, prior evidence of discriminative power in other neurodegenerative diseases, and its anatomical proximity to the brainstem as an important site of neurodegeneration. Using a discovery-based approach, we profiled protein abundance in TF of 49 ALS patients and 54 controls via data-independent acquisition mass spectrometry (DIA-MS) Biostatistical analysis and machine learning identified a signature of six proteins with diagnostic potential (AUROC = 66.2%).