Falls are common in patients with cerebellar ataxia (CA). Identification of gait variables associated with a higher risk of falls allows us to detect fallers and initiate protective procedures early. Gait variability, which is increased in CA patients, is a good predictor of falls in elderly subjects and patients with neurodegenerative diseases. The relationship between gait variability and fall risk in patients with different cerebellar disorders was systematically investigated. A total of 48 patients with different cerebellar ataxia entities [adult-onset cerebellar atrophy (SAOA) (n = 23), unknown entity (n = 7), vascular (n = 5), post-cerebellitis (n = 6), congenital (n = 2), Louis-Bar syndrome (n = 2), ethyltoxic (n = 2) posttraumatic (n = 1)] were examined using a GAITRite® sensor mat. Spatial and temporal variability parameters were used for ANOVA testing and logistic regression models with categorized fall events as dependent variables. Gait variability in the fore-aft direction showed significant differences between the fall groups (p < 0.05-0.01). Model effects were highest for walking with slow speed (correct prediction 0.50-0.72). The speed-dependent integral of gait variability markers showed a higher discriminatory power (correct prediction 0.74-0.94). Gait variability is linked to the fall risk of patients with CA, slow walking and temporal gait variability being most relevant. The use of speed-dependent integrals of gait variability improves the accuracy of fall prediction. To predict fall risks in cerebellar ataxia, gait variability measurements made during slow walking should be included in a gait analysis procedure. The effects of speed-adjusted physiotherapeutic interventions have to be further investigated.