How to predict unknown(hidden) value by incomplete value or partly recorded value Let me make it clear by make an example:

Suppose I knew a person's cost each month for 3 years like: 

2016Jan : $2500    

2016Feb : $4000    

2016Mar : $3500
...

Just according to this, can I predict how much he earned each month in these years? If I could, what model should use? If I couldn't, what info I need to make this possible. If I couldn't guess in 100 percent but I could guess by some probability, what model should I use?

Another example: 
Need to estimate how much each store sells in each city, however I could only got the sales when they record it in electric system, if they didn't record it in electric system(may use paper or something else); then I don't know, how can I get all sales, not just the sales record in electric system?

Any suggestion is welcomed
Actually you can use almost any regression model. When you do not want to go too much into theory simply use a gaussian process provided by sklearn. This model gives you predictions and uncertainties.