I tried both techniques but I was looking for something better

There is no magic way around the fact that the future values of explanatory variables are unknown, just as the future values of the variable of direct interest are unknown. You could use a vector autoregression to forecast all of the variables together or (as Tylerr suggested) have individual predictive models for each variable. Or if you have expert forecasts available, you could use those, too.

I tried both techniques but I was looking for something better

There is no magic way around the fact that the future values of explanatory variables are unknown, just as the future values of the variable of direct interest are unknown. You could use a vector autoregression to forecast all of the variables together or (as Tylerr suggested) have individual predictive models for each variable. Or if you have expert forecasts available, you could use those, too.

Also, note what Chris Haug points out: including an explanatory variable that is hard to forecast is not guaranteed to improve the forecast of the variable of direct interest. Only if you can forecast the explanatory variable with sufficient precision may it be worth retaining it in the predictive model.