Monthly data versus yearly prediction
You could consider each month as an explanatory variable. And the year as response variable. Because, for each year, you'll have 12 monthly variables.

With a model, you could find the relationship that has each month value with the final output. For that, you can perform a linear model (your categorical variables will or must be recoded as dummy variables for that estimation).

If you want to check the effect of the variable by itself. Yearly Target = a * Monthly Variable. I agree with @Leevo.