The last decade has been marked by a growing interest in an employment of intravenous cell delivery for treatment of neurological disorders. Numerous preclinical experimental studies have reported functional benefits, and have recently been followed by clinical trials. Some early clinical studies have indicated only modest positive effects, suggesting that the optimal conditions have not been defined yet. Thus, the evaluation of factors that influence outcomes, on the level of the whole population of preclinical studies by advanced statistical analysis, is warranted. PubMed search was conducted from the inception through 2006, and 60 preclinical studies were found and subjected to analysis. Categorical and continuous independent variables (IVs) were extracted. Three distinct outcomes of interest were selected as dependent variables (DVs) and named treatment effects: morphological, behavioral, and molecular, respectively. Mean outcomes, standard deviations (SDs), and animal numbers were retrieved and calculated by individual comparisons of experimental and control groups, based on the Hedges g formula, and were expressed as effect sizes (ESs) and variances. Publication bias and homogeneity were evaluated. The mainspring analyses were performed under a random effect model using Proc Mixed (SAS, version 9.2). A significant heterogeneity and publication bias were found. The ES pooling revealed large treatment effects. Univariate and multivariate meta-regression revealed that cell-related variables explained most of the heterogeneity. Cells retrieved from established lines and genetic modification of cells warrants the highest efficiency, in a dose-dependent manner. The stratified analysis of molecular effect measures revealed that apoptosis inhibition is the strongest brain tissue-positive change induced by cell therapy.