Manufacturing plants in Ghana face challenges related to system adoption, which can impact productivity and innovation. A time-series forecasting model was applied using historical data from selected manufacturing firms. Robust standard errors were used to account for uncertainty in forecasts. Manufacturing system adoption showed a consistent upward trend over the past five years, with an average growth rate of 5% per annum. The time-series model effectively predicted future adoption rates based on historical data and identified key drivers influencing system uptake. Implementing regular training programmes and monitoring systems can further enhance adoption rates in Ghanaian manufacturing sectors. Manufacturing Systems, Adoption Rates, Time-Series Forecasting, Ghana Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.