Is ARIMA appropriate for time series prediction involving a mix of explanatory and independent variables? I have a table with the following columns:

Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed

Quantity_Needed is the dependent variable that is numerical.

I want to predict Quantity_Needed and train a model using the columns mentioned above; however, I also want Quantity_Needed to train the model.

I have data from the past 5 years -> so I would have roughly 60 rows of data for one item.

Is it possible to use ARIMA for this?

If it is, what should I do next to build my model?
The correct name of what you are looking for is: ARIMAX, the ARIMA model works without covariables, the X (exogenous variables) include the possibility of having other explanatory variables.