Background: This study investigated the effect of the level of silica nanoparticles (SiO2NPs) crystallization on the cell proliferation of MRC-5 cells and its prediction using an artificial neural network (ANN).Methods: Variables studied included temperature (70-1000°C), calcination time (2, 12 and 24 hours), and catalyst feed rate (0.01, 0.05 and 0.1mL/min). Cell proliferation was determined by the MTT test after 24 hours of exposure, and results were analyzed using the t-test in MATLAB.Results: the synthesized particles size was less than 50nm, and the XRD peak varied from 30 to 21° during the increase in calcination temperature. The maximum level of crystallization was at 800°C (58% relative to amorphous) with the lowest cell viability. Cell proliferation decreased with increasing concentration of nanoparticles (p<0.05) and increasing feed rate. There was also a positive relationship between increased crystallization and decreased cell proliferation (R2=0.78), but no such association was observed for calcination time. Cell proliferation of MRC-5 was slightly correlated with the linear regression model (MSE>0.12), while ANN was well predicted by the Levenberg–Marquardt algorithm. The suggested structure in this study was 4:10:1 with R2all=0.97, R2test=0.97, RMSE=0.25 and MSE=0.003. The correlation between laboratory results and ANN prediction was 0.94, and the minimum and maximum OD level in the laboratory data and predicted ANN were attributed to 20 and 13 runs.Conclusion: changes in the degree of crystallization of SiO2NPs, an increase in concentration, and the rate of catalyst feed during crystallization of SiO2NPs were practical factors in increasing cytotoxicity.