Background: In this study, Multiple Linear Regression (MLR) is cast-off a statistical technique accustomed to propositions on determining the nexus between internal dynamic exasperations (IDEs) and external dynamic exasperations (EDEs), denoted as the independent variables (Xs), as well as perceived attitudes signified as the predictor variable for actual adoption (AA) of enterprise application architecture (EAA), presented as the dependent variable (Y). Objective: The objective of this paper was to ascertain the alternative hypotheses that IDEs, EDEs, and perceived attitudes (PAs) affect the AA of EAA for supply chain management (SCM) within small and medium enterprises (SMEs). Design/Methodology: The study used quantitative analysis chronicled in statistical package social science (SPSS) version 25 that encompassed diagnostic tests through Cronbach’s Alpha for reliability, and Double-Exponent Distribution for data validity. Data analysis is concerted through the model summary, graphical expression of MLR, regression analysis (algebra expression), along with Beta weight. Results/Findings: A stratified-random sampling of 310 data sets were used as SMEs’ owners and managers. The results were obtained from the main analysis of multiple regression that produced a model equation (Y) that determined the estimations of AA of EAA with 5xs; 19.49x6; 17.84x6; 18.23x6; 16.12x6; and 9.82x6; and response variable (Y); 25.8 x6: wherein Ԑi is residual error. Practical implications and conclusions: This exertion contributes to existing knowledge on AA of EAA for SCM by providing three main separable functions of multilinear regression (MLR). First, it broadens the understanding of the strength of relationships between Xs, PV and Y. Second, its expositions which predictors in the model are statistically significant and which are not. Third, it projects a confidence interval for each predicted regression coefficient.