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Background Atherosclerosis is a chronic inflammatory process that occurs in the arterial wall. This immuno-inflammatory process plays a role throughout all stages of stroke. Neutrophils, lymphocytes, and platelets are crucial blood cells for innate and adaptive immunity. This study investigated the associations of four types of immuno-inflammatory markers, namely the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and neutrophil count (NC), with clinical outcomes in patients with acute ischemic stroke. Methods In this retrospective study, we enrolled 2903 inpatients with acute ischemic stroke from May 2010 to May 2019. Data included risk factors, laboratory parameters, and clinical features during hospitalization. The National Institutes of Health Stroke Scale (NIHSS), and modified Rankin Scale (mRS) were used to assess stroke severity and outcomes. Results All four immuno-inflammatory markers exhibited positive linear correlations with age, glucose, creatinine, length of hospital stay, NIHSS score on admission, and mRS score at discharge. The levels of the four immuno-inflammatory markers were significantly higher in patients with large-artery atherosclerosis and cardioembolism and were highest in patients with other determined etiology. Patients with levels of immuno-inflammatory markers higher than their cutoff values for unfavorable outcomes also exhibited higher rates of cancer history (except for SII and NC), uremia (except for NC), elevated troponin I, and in-hospital complications. Multivariate analysis including SII revealed that admission NIHSS score ≥ 5, age > 75 years, SII > 724, diabetes mellitus, female sex, elevated troponin I, heart disease, and prior stroke were significant predictors for unfavorable outcomes. These significant predictors were retained after replacing SII > 724 with NLR > 143, PLR > 3.5, or NC > 6 × 10 3 /mL, except for prior stroke. For a basic model comprising seven significant predictors of unfavorable outcomes, the C-statistic was 0.860. The addition of SII, NLR, and PLR to the basic model resulted in a significant improvement in the prediction performance to 0.864, 0.863, and 0.863, respectively. Conclusions Immuno-inflammatory markers provide more useful information than conventional risk factors and other laboratory parameters for the prediction of stroke outcomes. SII > 724 is the most appropriate marker when combined with other predictors.