Journal of Materials Science Research and Reviews

California Bearing Ratio (CBR) test is a common laboratory test, performed to evaluate the shear strength and stiffness modulus of sub grade for the design of pavement. CBR test is a laborious test, therefore it is vital to develop the models for quick assessment of CBR. This study investigates the development of a mathematical model to estimate Soaked California Bearing Ratio of a lateritic soil. This research use Multiple Linear Regression (MLR) with R. studio software with a view to correlate Soaked California Bearing Ratio (SCBR) for the measured index properties. To achieve the objectives of this study, 20 soil samples were obtained with 4 samples representing a Local government. R programming studio Software version has been used to develop a mathematical model for the MLR. The experimental data and predictive models were developed in terms of liquid limit (LL), plasticity index (PI) Maximum Dry Density and percentages of fines, Gravel, and Sand respectively. The results from the index properties characterized the study area as Clayey soils (A-4, A-6 and A-7-5) and Silty or Clayey gravelling soils (A-2-6,A-2-7) according to AASHTO classification system The soil strength assessment indicates that the soils samples from all the Zones fell within the minimum dry density recommended for subgrade materials, stabilization is recommended for its suitability for either sub base or base course material for future contractor around this study area, this will savage haulage expenses when material are move from far distance to the site of work. The strengths of the developed Multiple Linear Regression (MLR) models have been examined in terms of regression coefficient of determination (R2). It is found that the correlation give a predictive power of 70%. The residual plotted on histogram curve is symmetrical in nature indicating normality of residual value.