ML technique to predict next year output based on text quantities
I'm not sure machine learning is the right method to count the number of arguments in a list. You can just write a function that does that and it's all you need...

Now if you want to predict the number of total components, assuming it holds some kind of temporal relation, there are a few techniques possible. But remember: Garbage in, Garbage out...

The easiest is to build a regression model by using past numbers as features, this gives an equation like this:

$$Y_t = a_1 \times Y_{t-1} + a_2 \times Y_{t-2} + ... + b$$

Next you can look at time series (ARIMA, SARIMA), which are a bit more advanced: additional to the time steps, they can take moving average and seasonal components into account.

And finally, you can also look at neural networks. If you have enough, and more importantly meaningful data, you can look at multilayer perceptron with a time window, 1d-convolutions and RNN/LSTM... Plenty resources exist if you want to go with this.