We previously discovered microRNAs (miRNAs) in cerebrospinal fluid (CSF) that differentiate Alzheimer's disease (AD) patients from Controls. Here we examined the performance of 37 candidate AD miRNA biomarkers in a new and independent cohort of CSF from 47 AD patients and 71 Controls on custom TaqMan arrays. We employed a consensus ranking approach to provide an overall priority score for each miRNA, then used multimarker models to assess the relative contributions of the top-ranking miRNAs to differentiate AD from Controls. We assessed classification performance of the top-ranking miRNAs when combined with apolipoprotein E4 (APOE4) genotype status or CSF amyloid-β42 (Aβ42):total tau (T-tau) measures. We also assessed whether miRNAs that ranked higher as AD markers correlate with Mini-Mental State Examination (MMSE) scores. We show that of 37 miRNAs brought forth from the discovery study, 26 miRNAs remained viable as candidate biomarkers for AD in the validation study. We found that combinations of 6-7 miRNAs work better to identify AD than subsets of fewer miRNAs. Of 26 miRNAs that contribute most to the multimarker models, 14 have higher potential than the others to predict AD. Addition of these 14 miRNAs to APOE4 status or CSF Aβ42:T-tau measures significantly improved classification performance for AD. We further show that individual miRNAs that ranked higher as AD markers correlate more strongly with changes in MMSE scores. Our studies validate that a set of CSF miRNAs serve as biomarkers for AD, and support their advancement toward development as biomarkers in the clinical setting.